初始化项目,由ModelHub XC社区提供模型
Model: huihui-ai/Huihui-granite-4.1-3b-abliterated Source: Original Platform
This commit is contained in:
36
.gitattributes
vendored
Normal file
36
.gitattributes
vendored
Normal file
@@ -0,0 +1,36 @@
|
|||||||
|
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ftz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.gz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.h5 filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.joblib filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.model filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.onnx filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.ot filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.parquet filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pb filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||||
|
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tflite filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.tgz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||||
|
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||||
|
ggml-model-bf16.gguf filter=lfs diff=lfs merge=lfs -text
|
||||||
250
README.md
Normal file
250
README.md
Normal file
@@ -0,0 +1,250 @@
|
|||||||
|
---
|
||||||
|
license: apache-2.0
|
||||||
|
library_name: transformers
|
||||||
|
base_model:
|
||||||
|
- ibm-granite/granite-4.1-3b
|
||||||
|
tags:
|
||||||
|
- language
|
||||||
|
- granite-4.1
|
||||||
|
- abliterated
|
||||||
|
- uncensored
|
||||||
|
---
|
||||||
|
|
||||||
|
# huihui-ai/Huihui-granite-4.1-3b-abliterated
|
||||||
|
|
||||||
|
|
||||||
|
This is an uncensored version of [ibm-granite/granite-4.1-3b](https://huggingface.co/ibm-granite/granite-4.1-3b) created with abliteration (see [remove-refusals-with-transformers](https://github.com/Sumandora/remove-refusals-with-transformers) to know more about it).
|
||||||
|
This is a crude, proof-of-concept implementation to remove refusals from an LLM model without using TransformerLens.
|
||||||
|
|
||||||
|
## ollama
|
||||||
|
|
||||||
|
Please use the latest version of [ollama](https://github.com/ollama/ollama/releases/tag)
|
||||||
|
|
||||||
|
You can use [huihui_ai/granite4.1-abliterated:3b](https://ollama.com/huihui_ai/granite4.1-abliterated:3b) directly,
|
||||||
|
|
||||||
|
```
|
||||||
|
ollama run huihui_ai/granite4.1-abliterated:3b
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
|
## Usage
|
||||||
|
You can use this model in your applications by loading it with Hugging Face's `transformers` library:
|
||||||
|
|
||||||
|
|
||||||
|
```python
|
||||||
|
|
||||||
|
#!/usr/bin/env python
|
||||||
|
# -*- coding: utf-8 -*-
|
||||||
|
|
||||||
|
import argparse
|
||||||
|
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
|
||||||
|
import torch
|
||||||
|
import os
|
||||||
|
import signal
|
||||||
|
import time
|
||||||
|
|
||||||
|
def parse_args():
|
||||||
|
parser = argparse.ArgumentParser(
|
||||||
|
description="Merge LoRA weights into huihui-ai/Huihui-granite-4.1-3b-abliterated base model and save the full model."
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--base_model",
|
||||||
|
type=str,
|
||||||
|
default="huihui-ai/Huihui-granite-4.1-3b-abliterated",
|
||||||
|
help="HuggingFace repo or local path of the base model.",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--dtype",
|
||||||
|
type=str,
|
||||||
|
default="bfloat16",
|
||||||
|
choices=["auto", "float16", "bfloat16", "float32"],
|
||||||
|
help="Data type for loading the base model (default: bfloat16).",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--device_map",
|
||||||
|
type=str,
|
||||||
|
default="auto",
|
||||||
|
help="Device map for model loading (e.g. 'cpu', 'auto').",
|
||||||
|
)
|
||||||
|
return parser.parse_args()
|
||||||
|
|
||||||
|
def main():
|
||||||
|
cpu_count = os.cpu_count()
|
||||||
|
print(f"Number of CPU cores in the system: {cpu_count}")
|
||||||
|
half_cpu_count = cpu_count // 2
|
||||||
|
os.environ["MKL_NUM_THREADS"] = str(half_cpu_count)
|
||||||
|
os.environ["OMP_NUM_THREADS"] = str(half_cpu_count)
|
||||||
|
torch.set_num_threads(half_cpu_count)
|
||||||
|
|
||||||
|
print(f"PyTorch threads: {torch.get_num_threads()}")
|
||||||
|
print(f"MKL threads: {os.getenv('MKL_NUM_THREADS')}")
|
||||||
|
print(f"OMP threads: {os.getenv('OMP_NUM_THREADS')}")
|
||||||
|
|
||||||
|
args = parse_args()
|
||||||
|
|
||||||
|
# Load the model and tokenizer
|
||||||
|
print(f"Load Model {args.base_model} ... ")
|
||||||
|
|
||||||
|
torch_dtype = {
|
||||||
|
"auto": "auto",
|
||||||
|
"float16": torch.float16,
|
||||||
|
"bfloat16": torch.bfloat16,
|
||||||
|
"float32": torch.float32,
|
||||||
|
}[args.dtype]
|
||||||
|
|
||||||
|
model = AutoModelForCausalLM.from_pretrained(
|
||||||
|
args.base_model,
|
||||||
|
dtype=torch_dtype,
|
||||||
|
device_map=args.device_map,
|
||||||
|
trust_remote_code=True,
|
||||||
|
)
|
||||||
|
|
||||||
|
tokenizer = AutoTokenizer.from_pretrained(args.base_model)
|
||||||
|
|
||||||
|
class CustomTextStreamer(TextStreamer):
|
||||||
|
def __init__(self, tokenizer, skip_prompt=True, skip_special_tokens=True):
|
||||||
|
super().__init__(tokenizer, skip_prompt=skip_prompt, skip_special_tokens=skip_special_tokens)
|
||||||
|
self.generated_text = ""
|
||||||
|
self.stop_flag = False
|
||||||
|
self.init_time = time.time() # Record initialization time
|
||||||
|
self.end_time = None # To store end time
|
||||||
|
self.first_token_time = None # To store first token generation time
|
||||||
|
self.token_count = 0 # To track total tokens
|
||||||
|
|
||||||
|
def on_finalized_text(self, text: str, stream_end: bool = False):
|
||||||
|
if self.first_token_time is None and text.strip(): # Set first token time on first non-empty text
|
||||||
|
self.first_token_time = time.time()
|
||||||
|
if stream_end:
|
||||||
|
self.end_time = time.time() # Record end time when streaming ends
|
||||||
|
|
||||||
|
self.generated_text += text
|
||||||
|
self.token_count += 1
|
||||||
|
print(text, end="", flush=True)
|
||||||
|
|
||||||
|
if self.stop_flag:
|
||||||
|
raise StopIteration
|
||||||
|
|
||||||
|
def stop_generation(self):
|
||||||
|
self.stop_flag = True
|
||||||
|
self.end_time = time.time() # Record end time when generation is stopped
|
||||||
|
|
||||||
|
def get_metrics(self):
|
||||||
|
"""Returns initialization time, first token time, first token latency, end time, total time, total tokens, and tokens per second."""
|
||||||
|
if self.end_time is None:
|
||||||
|
self.end_time = time.time() # Set end time if not already set
|
||||||
|
total_time = self.end_time - self.init_time # Total time from init to end
|
||||||
|
tokens_per_second = self.token_count / total_time if total_time > 0 else 0
|
||||||
|
first_token_latency = (self.first_token_time - self.init_time) if self.first_token_time is not None else None
|
||||||
|
metrics = {
|
||||||
|
"init_time": self.init_time,
|
||||||
|
"first_token_time": self.first_token_time,
|
||||||
|
"first_token_latency": first_token_latency,
|
||||||
|
"end_time": self.end_time,
|
||||||
|
"total_time": total_time, # Total time in seconds
|
||||||
|
"total_tokens": self.token_count,
|
||||||
|
"tokens_per_second": tokens_per_second
|
||||||
|
}
|
||||||
|
return metrics
|
||||||
|
|
||||||
|
def generate_stream(model, tokenizer, messages, enable_thinking, skip_prompt, skip_special_tokens, max_new_tokens):
|
||||||
|
text = tokenizer.apply_chat_template(
|
||||||
|
messages,
|
||||||
|
tokenize=False,
|
||||||
|
add_generation_prompt=True,
|
||||||
|
)
|
||||||
|
inputs = tokenizer(
|
||||||
|
text,
|
||||||
|
return_tensors="pt",
|
||||||
|
).to(model.device)
|
||||||
|
|
||||||
|
streamer = CustomTextStreamer(tokenizer, skip_prompt=skip_prompt, skip_special_tokens=skip_special_tokens)
|
||||||
|
|
||||||
|
def signal_handler(sig, frame):
|
||||||
|
streamer.stop_generation()
|
||||||
|
print("\n[Generation stopped by user with Ctrl+C]")
|
||||||
|
|
||||||
|
signal.signal(signal.SIGINT, signal_handler)
|
||||||
|
|
||||||
|
print("Response: ", end="", flush=True)
|
||||||
|
try:
|
||||||
|
generated_ids = model.generate(
|
||||||
|
**inputs,
|
||||||
|
max_new_tokens=max_new_tokens,
|
||||||
|
streamer=streamer)
|
||||||
|
|
||||||
|
del generated_ids
|
||||||
|
except StopIteration:
|
||||||
|
print("\n[Stopped by user]")
|
||||||
|
|
||||||
|
del inputs
|
||||||
|
torch.cuda.empty_cache()
|
||||||
|
signal.signal(signal.SIGINT, signal.SIG_DFL)
|
||||||
|
|
||||||
|
return streamer.generated_text, streamer.stop_flag, streamer.get_metrics()
|
||||||
|
|
||||||
|
messages = []
|
||||||
|
skip_prompt=True
|
||||||
|
skip_special_tokens=True
|
||||||
|
|
||||||
|
while True:
|
||||||
|
print(f"skip_prompt = {skip_prompt}.")
|
||||||
|
print(f"skip_special_tokens = {skip_special_tokens}.\n")
|
||||||
|
|
||||||
|
user_input = input("User: ").strip()
|
||||||
|
if user_input.lower() == "/exit":
|
||||||
|
print("Exiting chat.")
|
||||||
|
break
|
||||||
|
if user_input.lower() == "/clear":
|
||||||
|
messages = []
|
||||||
|
print("Chat history cleared. Starting a new conversation.")
|
||||||
|
continue
|
||||||
|
if user_input.lower() == "/skip_prompt":
|
||||||
|
skip_prompt = not skip_prompt
|
||||||
|
continue
|
||||||
|
if user_input.lower() == "/skip_special_tokens":
|
||||||
|
skip_special_tokens = not skip_special_tokens
|
||||||
|
continue
|
||||||
|
if not user_input:
|
||||||
|
print("Input cannot be empty. Please enter something.")
|
||||||
|
continue
|
||||||
|
|
||||||
|
messages.append({"role": "user", "content": user_input})
|
||||||
|
response, stop_flag, metrics = generate_stream(model, tokenizer, messages, enable_thinking, skip_prompt, skip_special_tokens, 40960)
|
||||||
|
print("\n\nMetrics:")
|
||||||
|
for key, value in metrics.items():
|
||||||
|
print(f" {key}: {value}")
|
||||||
|
|
||||||
|
print("", flush=True)
|
||||||
|
|
||||||
|
if stop_flag:
|
||||||
|
continue
|
||||||
|
messages.append({"role": "assistant", "content": response})
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
|
```
|
||||||
|
|
||||||
|
### Usage Warnings
|
||||||
|
|
||||||
|
|
||||||
|
- **Risk of Sensitive or Controversial Outputs**: This model’s safety filtering has been significantly reduced, potentially generating sensitive, controversial, or inappropriate content. Users should exercise caution and rigorously review generated outputs.
|
||||||
|
|
||||||
|
- **Not Suitable for All Audiences**: Due to limited content filtering, the model’s outputs may be inappropriate for public settings, underage users, or applications requiring high security.
|
||||||
|
|
||||||
|
- **Legal and Ethical Responsibilities**: Users must ensure their usage complies with local laws and ethical standards. Generated content may carry legal or ethical risks, and users are solely responsible for any consequences.
|
||||||
|
|
||||||
|
- **Research and Experimental Use**: It is recommended to use this model for research, testing, or controlled environments, avoiding direct use in production or public-facing commercial applications.
|
||||||
|
|
||||||
|
- **Monitoring and Review Recommendations**: Users are strongly advised to monitor model outputs in real-time and conduct manual reviews when necessary to prevent the dissemination of inappropriate content.
|
||||||
|
|
||||||
|
- **No Default Safety Guarantees**: Unlike standard models, this model has not undergone rigorous safety optimization. huihui.ai bears no responsibility for any consequences arising from its use.
|
||||||
|
|
||||||
|
|
||||||
|
### Donation
|
||||||
|
##### Your donation helps us continue our further development and improvement, a cup of coffee can do it.
|
||||||
|
- bitcoin:
|
||||||
|
```
|
||||||
|
bc1qqnkhuchxw0zqjh2ku3lu4hq45hc6gy84uk70ge
|
||||||
|
```
|
||||||
|
- Support our work on [Ko-fi](https://ko-fi.com/huihuiai)!
|
||||||
|
|
||||||
114
chat_template.jinja
Normal file
114
chat_template.jinja
Normal file
@@ -0,0 +1,114 @@
|
|||||||
|
{%- set tools_system_message_prefix = 'You are a helpful assistant with access to the following tools. You may call one or more tools to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>' %}
|
||||||
|
{%- set tools_system_message_suffix = '\n</tools>\n\nFor each tool call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call>. If a tool does not exist in the provided list of tools, notify the user that you do not have the ability to fulfill the request.' %}
|
||||||
|
{%- set documents_system_message_prefix = 'You are a helpful assistant with access to the following documents. You may use one or more documents to assist with the user query.\n\nYou are given a list of documents within <documents></documents> XML tags:\n<documents>' %}
|
||||||
|
{%- set documents_system_message_suffix = '\n</documents>\n\nWrite the response to the user\'s input by strictly aligning with the facts in the provided documents. If the information needed to answer the question is not available in the documents, inform the user that the question cannot be answered based on the available data.' %}
|
||||||
|
{%- if available_tools is defined and available_tools %}
|
||||||
|
{%- set tools = available_tools %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- set ns = namespace(tools_system_message=tools_system_message_prefix,
|
||||||
|
documents_system_message=documents_system_message_prefix,
|
||||||
|
system_message=''
|
||||||
|
) %}
|
||||||
|
{%- if tools %}
|
||||||
|
{%- for tool in tools %}
|
||||||
|
{%- set ns.tools_system_message = ns.tools_system_message + '\n' + (tool | tojson) %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- set ns.tools_system_message = ns.tools_system_message + tools_system_message_suffix %}
|
||||||
|
{%- else %}
|
||||||
|
{%- set ns.tools_system_message = '' %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if documents %}
|
||||||
|
{%- for document in documents %}
|
||||||
|
{%- set ns.documents_system_message = ns.documents_system_message + '\n' + (document | tojson) %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- set ns.documents_system_message = ns.documents_system_message + documents_system_message_suffix %}
|
||||||
|
{%- else %}
|
||||||
|
{%- set ns.documents_system_message = '' %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if messages[0].role == 'system' %}
|
||||||
|
{%- if messages[0].content is string %}
|
||||||
|
{%- set ns.system_message = messages[0].content %}
|
||||||
|
{%- elif messages[0].content is iterable %}
|
||||||
|
{%- for entry in messages[0].content %}
|
||||||
|
{%- if entry.type== 'text' %}
|
||||||
|
{%- if ns.system_message != '' %}
|
||||||
|
{%- set ns.system_message = ns.system_message + '\n' %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- set ns.system_message = ns.system_message + entry.text %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if tools and documents %}
|
||||||
|
{%- set ns.system_message = ns.system_message + '\n\n' + ns.tools_system_message + '\n\n' + ns.documents_system_message %}
|
||||||
|
{%- elif tools %}
|
||||||
|
{%- set ns.system_message = ns.system_message + '\n\n' + ns.tools_system_message %}
|
||||||
|
{%- elif documents %}
|
||||||
|
{%- set ns.system_message = ns.system_message + '\n\n' + ns.documents_system_message %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- else %}
|
||||||
|
{%- if tools and documents %}
|
||||||
|
{%- set ns.system_message = ns.tools_system_message + '\n\n' + ns.documents_system_message %}
|
||||||
|
{%- elif tools %}
|
||||||
|
{%- set ns.system_message = ns.tools_system_message %}
|
||||||
|
{%- elif documents %}
|
||||||
|
{%- set ns.system_message = ns.documents_system_message %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if ns.system_message %}
|
||||||
|
{{- '<|start_of_role|>system<|end_of_role|>' + ns.system_message + '<|end_of_text|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- for message in messages %}
|
||||||
|
{%- set content = namespace(val='') %}
|
||||||
|
{%- if message.content is string %}
|
||||||
|
{%- set content.val = message.content %}
|
||||||
|
{%- else %}
|
||||||
|
{%- if message.content is iterable %}
|
||||||
|
{%- for entry in message.content %}
|
||||||
|
{%- if entry.type== 'text' %}
|
||||||
|
{%- if content.val != '' %}
|
||||||
|
{%- set content.val = content.val + '\n' %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- set content.val = content.val + entry.text %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if (message.role == 'user') or (message.role == 'system' and not loop.first) %}
|
||||||
|
{{- '<|start_of_role|>' + message.role + '<|end_of_role|>' + content.val + '<|end_of_text|>\n' }}
|
||||||
|
{%- elif message.role == 'assistant' %}
|
||||||
|
{{- '<|start_of_role|>' + message.role + '<|end_of_role|>' + content.val }}
|
||||||
|
{%- if message.tool_calls %}
|
||||||
|
{%- for tool_call in message.tool_calls %}
|
||||||
|
{%- if (loop.first and content.val) or (not loop.first) %}
|
||||||
|
{{- '\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- if tool_call.function %}
|
||||||
|
{%- set tool_call = tool_call.function %}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '<tool_call>\n{"name": "' }}
|
||||||
|
{{- tool_call.name }}
|
||||||
|
{{- '", "arguments": ' }}
|
||||||
|
{%- if tool_call.arguments is string %}
|
||||||
|
{{- tool_call.arguments }}
|
||||||
|
{%- else %}
|
||||||
|
{{- tool_call.arguments | tojson }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '}\n</tool_call>' }}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '<|end_of_text|>\n' }}
|
||||||
|
{%- elif message.role == 'tool' %}
|
||||||
|
{%- if loop.first or (messages[loop.index0 - 1].role != 'tool') %}
|
||||||
|
{{- '<|start_of_role|>user<|end_of_role|>' }}
|
||||||
|
{%- endif %}
|
||||||
|
{{- '\n<tool_response>\n' }}
|
||||||
|
{{- content.val }}
|
||||||
|
{{- '\n</tool_response>' }}
|
||||||
|
{%- if loop.last or (messages[loop.index0 + 1].role != 'tool') %}
|
||||||
|
{{- '<|end_of_text|>\n' }}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endif %}
|
||||||
|
{%- endfor %}
|
||||||
|
{%- if add_generation_prompt %}
|
||||||
|
{{- '<|start_of_role|>assistant<|end_of_role|>' }}
|
||||||
|
{%- endif %}
|
||||||
32
config.json
Normal file
32
config.json
Normal file
@@ -0,0 +1,32 @@
|
|||||||
|
{
|
||||||
|
"architectures": [
|
||||||
|
"GraniteForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_bias": false,
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"attention_multiplier": 0.015625,
|
||||||
|
"bos_token_id": 100257,
|
||||||
|
"embedding_multiplier": 12.0,
|
||||||
|
"eos_token_id": 100257,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2560,
|
||||||
|
"initializer_range": 0.1,
|
||||||
|
"intermediate_size": 8192,
|
||||||
|
"logits_scaling": 10.0,
|
||||||
|
"max_position_embeddings": 131072,
|
||||||
|
"mlp_bias": false,
|
||||||
|
"model_type": "granite",
|
||||||
|
"num_attention_heads": 40,
|
||||||
|
"num_hidden_layers": 40,
|
||||||
|
"num_key_value_heads": 8,
|
||||||
|
"pad_token_id": 100256,
|
||||||
|
"residual_multiplier": 0.22,
|
||||||
|
"rms_norm_eps": 1e-05,
|
||||||
|
"rope_scaling": null,
|
||||||
|
"rope_theta": 10000000,
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"torch_dtype": "bfloat16",
|
||||||
|
"transformers_version": "4.53.3",
|
||||||
|
"use_cache": true,
|
||||||
|
"vocab_size": 100352
|
||||||
|
}
|
||||||
7
generation_config.json
Normal file
7
generation_config.json
Normal file
@@ -0,0 +1,7 @@
|
|||||||
|
{
|
||||||
|
"_from_model_config": true,
|
||||||
|
"bos_token_id": 100257,
|
||||||
|
"eos_token_id": 100257,
|
||||||
|
"pad_token_id": 100256,
|
||||||
|
"transformers_version": "4.53.3"
|
||||||
|
}
|
||||||
3
ggml-model-bf16.gguf
Normal file
3
ggml-model-bf16.gguf
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:12d6f2128e9aa113c1c6ee6a9a24678dc53fccbb3e84bca5165c58ea5f4b14cc
|
||||||
|
size 6809656064
|
||||||
100001
merges.txt
Normal file
100001
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
3
model-00001-of-00002.safetensors
Normal file
3
model-00001-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:6e427afab9e8f757332e398a5b846e5d181ccfc3801e19e2f7273c91717aec66
|
||||||
|
size 4991538312
|
||||||
3
model-00002-of-00002.safetensors
Normal file
3
model-00002-of-00002.safetensors
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:fa1d23fe546c6bf9220555d9aaccf23b7fd475cb968ebed10d52a8fe693dfdf5
|
||||||
|
size 1814176416
|
||||||
370
model.safetensors.index.json
Normal file
370
model.safetensors.index.json
Normal file
@@ -0,0 +1,370 @@
|
|||||||
|
{
|
||||||
|
"metadata": {
|
||||||
|
"total_parameters": 3402836480,
|
||||||
|
"total_size": 6805672960
|
||||||
|
},
|
||||||
|
"weight_map": {
|
||||||
|
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.28.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.29.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.29.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.30.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.32.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.33.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.34.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.35.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.36.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.37.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.38.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.39.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||||
|
"model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.down_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.gate_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.mlp.up_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.post_attention_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.o_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||||
|
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||||
|
}
|
||||||
|
}
|
||||||
429
model_params1.txt
Normal file
429
model_params1.txt
Normal file
@@ -0,0 +1,429 @@
|
|||||||
|
ibm-granite/granite-4.1-3b
|
||||||
|
------------------------------------------------------------
|
||||||
|
GraniteForCausalLM(
|
||||||
|
(model): GraniteModel(
|
||||||
|
(embed_tokens): Embedding(100352, 2560, padding_idx=100256)
|
||||||
|
(layers): ModuleList(
|
||||||
|
(0-39): 40 x GraniteDecoderLayer(
|
||||||
|
(self_attn): GraniteAttention(
|
||||||
|
(q_proj): Linear(in_features=2560, out_features=2560, bias=False)
|
||||||
|
(k_proj): Linear(in_features=2560, out_features=512, bias=False)
|
||||||
|
(v_proj): Linear(in_features=2560, out_features=512, bias=False)
|
||||||
|
(o_proj): Linear(in_features=2560, out_features=2560, bias=False)
|
||||||
|
)
|
||||||
|
(mlp): GraniteMLP(
|
||||||
|
(gate_proj): Linear(in_features=2560, out_features=8192, bias=False)
|
||||||
|
(up_proj): Linear(in_features=2560, out_features=8192, bias=False)
|
||||||
|
(down_proj): Linear(in_features=8192, out_features=2560, bias=False)
|
||||||
|
(act_fn): SiLUActivation()
|
||||||
|
)
|
||||||
|
(input_layernorm): GraniteRMSNorm((2560,), eps=1e-05)
|
||||||
|
(post_attention_layernorm): GraniteRMSNorm((2560,), eps=1e-05)
|
||||||
|
)
|
||||||
|
)
|
||||||
|
(norm): GraniteRMSNorm((2560,), eps=1e-05)
|
||||||
|
(rotary_emb): GraniteRotaryEmbedding()
|
||||||
|
)
|
||||||
|
(lm_head): Linear(in_features=2560, out_features=100352, bias=False)
|
||||||
|
)
|
||||||
|
------------------------------------------------------------
|
||||||
|
GraniteConfig {
|
||||||
|
"architectures": [
|
||||||
|
"GraniteForCausalLM"
|
||||||
|
],
|
||||||
|
"attention_bias": false,
|
||||||
|
"attention_dropout": 0.0,
|
||||||
|
"attention_multiplier": 0.015625,
|
||||||
|
"bos_token_id": 100257,
|
||||||
|
"dtype": "bfloat16",
|
||||||
|
"embedding_multiplier": 12.0,
|
||||||
|
"eos_token_id": 100257,
|
||||||
|
"hidden_act": "silu",
|
||||||
|
"hidden_size": 2560,
|
||||||
|
"initializer_range": 0.1,
|
||||||
|
"intermediate_size": 8192,
|
||||||
|
"logits_scaling": 10.0,
|
||||||
|
"max_position_embeddings": 131072,
|
||||||
|
"mlp_bias": false,
|
||||||
|
"model_type": "granite",
|
||||||
|
"num_attention_heads": 40,
|
||||||
|
"num_hidden_layers": 40,
|
||||||
|
"num_key_value_heads": 8,
|
||||||
|
"pad_token_id": 100256,
|
||||||
|
"residual_multiplier": 0.22,
|
||||||
|
"rms_norm_eps": 1e-05,
|
||||||
|
"rope_parameters": {
|
||||||
|
"rope_theta": 10000000,
|
||||||
|
"rope_type": "default"
|
||||||
|
},
|
||||||
|
"tie_word_embeddings": true,
|
||||||
|
"transformers_version": "5.6.2",
|
||||||
|
"use_cache": true,
|
||||||
|
"vocab_size": 100352
|
||||||
|
}
|
||||||
|
|
||||||
|
------------------------------------------------------------
|
||||||
|
model.embed_tokens.weight: dtype:torch.bfloat16, shape:torch.Size([100352, 2560]), size:256,901,120, device: cuda:0
|
||||||
|
model.layers.0.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.0.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.0.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.0.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.0.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.0.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.0.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.0.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.0.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.1.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.1.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.1.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.1.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.1.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.1.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.1.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.1.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.1.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.2.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.2.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.2.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.2.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.2.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.2.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.2.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.2.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.2.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.3.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.3.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.3.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.3.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.3.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.3.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.3.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.3.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.3.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.4.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.4.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.4.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.4.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.4.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.4.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.4.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.4.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.4.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.5.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.5.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.5.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.5.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.5.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.5.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.5.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.5.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.5.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.6.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.6.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.6.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.6.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.6.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.6.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.6.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.6.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.6.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.7.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.7.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.7.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.7.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.7.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.7.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.7.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.7.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.7.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.8.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.8.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.8.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.8.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.8.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.8.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.8.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.8.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.8.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.9.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.9.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.9.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.9.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.9.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.9.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.9.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.9.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.9.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.10.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.10.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.10.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.10.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.10.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.10.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.10.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.10.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.10.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.11.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.11.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.11.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.11.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.11.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.11.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.11.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.11.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.11.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.12.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.12.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.12.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.12.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.12.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.12.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.12.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.12.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.12.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.13.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.13.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.13.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.13.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.13.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.13.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.13.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.13.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.13.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.14.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.14.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.14.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.14.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.14.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.14.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.14.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.14.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.14.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.15.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.15.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.15.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.15.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.15.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.15.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.15.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.15.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.15.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.16.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.16.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.16.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.16.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.16.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.16.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.16.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.16.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.16.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.17.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.17.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.17.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.17.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.17.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.17.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.17.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.17.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.17.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.18.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.18.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.18.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.18.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.18.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.18.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.18.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.18.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.18.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.19.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.19.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.19.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.19.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.19.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.19.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.19.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.19.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.19.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.20.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.20.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.20.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.20.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.20.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.20.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.20.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.20.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.20.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.21.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.21.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.21.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.21.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.21.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.21.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.21.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.21.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.21.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.22.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.22.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.22.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.22.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.22.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.22.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.22.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.22.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.22.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.23.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.23.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.23.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.23.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.23.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.23.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.23.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.23.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.23.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.24.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.24.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.24.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.24.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.24.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.24.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.24.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.24.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.24.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.25.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.25.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.25.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.25.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.25.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.25.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.25.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.25.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.25.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.26.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.26.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.26.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.26.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.26.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.26.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.26.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.26.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.26.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.27.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.27.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.27.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.27.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.27.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.27.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.27.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.27.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.27.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.28.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.28.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.28.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.28.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.28.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.28.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.28.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.28.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.28.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.29.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.29.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.29.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.29.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.29.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.29.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.29.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.29.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.29.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.30.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.30.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.30.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.30.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.30.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.30.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.30.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.30.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.30.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.31.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.31.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.31.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.31.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.31.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.31.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.31.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.31.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.31.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.32.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.32.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.32.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.32.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.32.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.32.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.32.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.32.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.32.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.33.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.33.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.33.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.33.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.33.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.33.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.33.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.33.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.33.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.34.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.34.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.34.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.34.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.34.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.34.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.34.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.34.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.34.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.35.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.35.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.35.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.35.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.35.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.35.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.35.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.35.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.35.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.36.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.36.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.36.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.36.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.36.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.36.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.36.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.36.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.36.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.37.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.37.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.37.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.37.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.37.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.37.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.37.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.37.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.37.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.38.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.38.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.38.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.38.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.38.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.38.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.38.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.38.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.38.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.39.self_attn.q_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.39.self_attn.k_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.39.self_attn.v_proj.weight: dtype:torch.bfloat16, shape:torch.Size([512, 2560]), size:1,310,720, device: cuda:0
|
||||||
|
model.layers.39.self_attn.o_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 2560]), size:6,553,600, device: cuda:0
|
||||||
|
model.layers.39.mlp.gate_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.39.mlp.up_proj.weight: dtype:torch.bfloat16, shape:torch.Size([8192, 2560]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.39.mlp.down_proj.weight: dtype:torch.bfloat16, shape:torch.Size([2560, 8192]), size:20,971,520, device: cuda:0
|
||||||
|
model.layers.39.input_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.layers.39.post_attention_layernorm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
model.norm.weight: dtype:torch.bfloat16, shape:torch.Size([2560]), size:2,560, device: cuda:0
|
||||||
|
------------------------------------------------------------
|
||||||
|
total_params: 3,402,836,480
|
||||||
362
sharded_ablate.log
Normal file
362
sharded_ablate.log
Normal file
@@ -0,0 +1,362 @@
|
|||||||
|
4, model.embed_tokens.weight, torch.Size([100352, 2560]), layer -1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.input_layernorm.weight, torch.Size([2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.0.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.post_attention_layernorm.weight, torch.Size([2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.0.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.0.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 0, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.input_layernorm.weight, torch.Size([2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.1.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.post_attention_layernorm.weight, torch.Size([2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.1.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.1.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 1, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.input_layernorm.weight, torch.Size([2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.10.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.post_attention_layernorm.weight, torch.Size([2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.10.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.10.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 10, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.input_layernorm.weight, torch.Size([2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.11.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.post_attention_layernorm.weight, torch.Size([2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.11.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.11.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 11, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.input_layernorm.weight, torch.Size([2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.12.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.post_attention_layernorm.weight, torch.Size([2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.12.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.12.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 12, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.input_layernorm.weight, torch.Size([2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.13.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.post_attention_layernorm.weight, torch.Size([2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.13.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.13.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 13, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.input_layernorm.weight, torch.Size([2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.14.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.post_attention_layernorm.weight, torch.Size([2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.14.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.14.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 14, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.input_layernorm.weight, torch.Size([2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.15.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.post_attention_layernorm.weight, torch.Size([2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.15.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.15.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 15, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.input_layernorm.weight, torch.Size([2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.16.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.post_attention_layernorm.weight, torch.Size([2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.16.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.16.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 16, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.input_layernorm.weight, torch.Size([2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.17.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.post_attention_layernorm.weight, torch.Size([2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.17.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.17.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 17, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.input_layernorm.weight, torch.Size([2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.18.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.post_attention_layernorm.weight, torch.Size([2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.18.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.18.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 18, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.input_layernorm.weight, torch.Size([2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.19.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.post_attention_layernorm.weight, torch.Size([2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.19.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.19.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 19, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.input_layernorm.weight, torch.Size([2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.2.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.post_attention_layernorm.weight, torch.Size([2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.2.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.2.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 2, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.input_layernorm.weight, torch.Size([2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.20.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.post_attention_layernorm.weight, torch.Size([2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.20.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.20.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 20, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.input_layernorm.weight, torch.Size([2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.21.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.post_attention_layernorm.weight, torch.Size([2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.21.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.21.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 21, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.input_layernorm.weight, torch.Size([2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.22.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.post_attention_layernorm.weight, torch.Size([2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.22.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.22.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 22, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.input_layernorm.weight, torch.Size([2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.23.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.post_attention_layernorm.weight, torch.Size([2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.23.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.23.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 23, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.input_layernorm.weight, torch.Size([2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.24.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.post_attention_layernorm.weight, torch.Size([2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.24.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.24.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 24, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.input_layernorm.weight, torch.Size([2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.25.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.post_attention_layernorm.weight, torch.Size([2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.25.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.25.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 25, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.input_layernorm.weight, torch.Size([2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.26.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.post_attention_layernorm.weight, torch.Size([2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.26.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.26.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 26, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.input_layernorm.weight, torch.Size([2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.27.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.post_attention_layernorm.weight, torch.Size([2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.27.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.27.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 27, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.28.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 28, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.28.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 28, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.28.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 28, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.28.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 28, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.28.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 28, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.input_layernorm.weight, torch.Size([2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.3.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.post_attention_layernorm.weight, torch.Size([2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.3.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.3.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 3, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.input_layernorm.weight, torch.Size([2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.4.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.post_attention_layernorm.weight, torch.Size([2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.4.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.4.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 4, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.input_layernorm.weight, torch.Size([2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.5.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.post_attention_layernorm.weight, torch.Size([2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.5.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.5.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 5, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.input_layernorm.weight, torch.Size([2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.6.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.post_attention_layernorm.weight, torch.Size([2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.6.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.6.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 6, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.input_layernorm.weight, torch.Size([2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.7.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.post_attention_layernorm.weight, torch.Size([2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.7.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.7.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 7, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.input_layernorm.weight, torch.Size([2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.8.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.post_attention_layernorm.weight, torch.Size([2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.8.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.8.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 8, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.input_layernorm.weight, torch.Size([2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
2, model.layers.9.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.post_attention_layernorm.weight, torch.Size([2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
1, model.layers.9.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.9.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 9, model-00001-of-00002.safetensors
|
||||||
|
3, model.layers.28.input_layernorm.weight, torch.Size([2560]), layer 28, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.28.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 28, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.28.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 28, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.28.post_attention_layernorm.weight, torch.Size([2560]), layer 28, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.input_layernorm.weight, torch.Size([2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.29.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.post_attention_layernorm.weight, torch.Size([2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.29.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.29.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 29, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.input_layernorm.weight, torch.Size([2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.30.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.post_attention_layernorm.weight, torch.Size([2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.30.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.30.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 30, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.input_layernorm.weight, torch.Size([2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.31.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.post_attention_layernorm.weight, torch.Size([2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.31.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.31.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 31, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.input_layernorm.weight, torch.Size([2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.32.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.post_attention_layernorm.weight, torch.Size([2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.32.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.32.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 32, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.input_layernorm.weight, torch.Size([2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.33.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.post_attention_layernorm.weight, torch.Size([2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.33.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.33.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 33, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.input_layernorm.weight, torch.Size([2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.34.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.post_attention_layernorm.weight, torch.Size([2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.34.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.34.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 34, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.input_layernorm.weight, torch.Size([2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.35.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.post_attention_layernorm.weight, torch.Size([2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.35.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.35.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 35, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.input_layernorm.weight, torch.Size([2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.36.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.post_attention_layernorm.weight, torch.Size([2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.36.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.36.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 36, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.input_layernorm.weight, torch.Size([2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.37.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.post_attention_layernorm.weight, torch.Size([2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.37.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.37.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 37, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.input_layernorm.weight, torch.Size([2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.38.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.post_attention_layernorm.weight, torch.Size([2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.38.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.38.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 38, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.input_layernorm.weight, torch.Size([2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
2, model.layers.39.mlp.down_proj.weight, torch.Size([2560, 8192]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.mlp.gate_proj.weight, torch.Size([8192, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.mlp.up_proj.weight, torch.Size([8192, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.post_attention_layernorm.weight, torch.Size([2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.self_attn.k_proj.weight, torch.Size([512, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
1, model.layers.39.self_attn.o_proj.weight, torch.Size([2560, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.self_attn.q_proj.weight, torch.Size([2560, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
3, model.layers.39.self_attn.v_proj.weight, torch.Size([512, 2560]), layer 39, model-00002-of-00002.safetensors
|
||||||
|
4, model.norm.weight, torch.Size([2560]), layer -1, model-00002-of-00002.safetensors
|
||||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
|||||||
|
{
|
||||||
|
"bos_token": {
|
||||||
|
"content": "<|end_of_text|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"eos_token": {
|
||||||
|
"content": "<|end_of_text|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"pad_token": {
|
||||||
|
"content": "<|pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
},
|
||||||
|
"unk_token": {
|
||||||
|
"content": "<|unk|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
}
|
||||||
|
}
|
||||||
501264
tokenizer.json
Normal file
501264
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
783
tokenizer_config.json
Normal file
783
tokenizer_config.json
Normal file
@@ -0,0 +1,783 @@
|
|||||||
|
{
|
||||||
|
"add_bos_token": false,
|
||||||
|
"add_prefix_space": false,
|
||||||
|
"added_tokens_decoder": {
|
||||||
|
"100256": {
|
||||||
|
"content": "<|pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100257": {
|
||||||
|
"content": "<|end_of_text|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100258": {
|
||||||
|
"content": "<|fim_prefix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100259": {
|
||||||
|
"content": "<|fim_middle|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100260": {
|
||||||
|
"content": "<|fim_suffix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100261": {
|
||||||
|
"content": "<|fim_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100262": {
|
||||||
|
"content": "<|filename|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100263": {
|
||||||
|
"content": "<|reponame|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100264": {
|
||||||
|
"content": "<|start_of_role|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100265": {
|
||||||
|
"content": "<|end_of_role|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100266": {
|
||||||
|
"content": "<|unused_1|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100267": {
|
||||||
|
"content": "<|start_of_plugin|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100268": {
|
||||||
|
"content": "<|end_of_plugin|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100269": {
|
||||||
|
"content": "<|unk|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100270": {
|
||||||
|
"content": "<tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100271": {
|
||||||
|
"content": "</tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100272": {
|
||||||
|
"content": "<tool_response>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100273": {
|
||||||
|
"content": "</tool_response>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100274": {
|
||||||
|
"content": "<think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100275": {
|
||||||
|
"content": "</think>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"100276": {
|
||||||
|
"content": "<think_on>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100277": {
|
||||||
|
"content": "<think_off>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100278": {
|
||||||
|
"content": "<schema>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100279": {
|
||||||
|
"content": "</schema>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100280": {
|
||||||
|
"content": "<tools>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100281": {
|
||||||
|
"content": "</tools>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100282": {
|
||||||
|
"content": "<documents>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100283": {
|
||||||
|
"content": "</documents>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100284": {
|
||||||
|
"content": "<|unused_15|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100285": {
|
||||||
|
"content": "<|unused_16|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100286": {
|
||||||
|
"content": "<|unused_17|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100287": {
|
||||||
|
"content": "<|unused_18|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100288": {
|
||||||
|
"content": "<|unused_19|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100289": {
|
||||||
|
"content": "<|unused_20|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100290": {
|
||||||
|
"content": "<|unused_21|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100291": {
|
||||||
|
"content": "<|unused_22|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100292": {
|
||||||
|
"content": "<|unused_23|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100293": {
|
||||||
|
"content": "<|unused_24|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100294": {
|
||||||
|
"content": "<|unused_25|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100295": {
|
||||||
|
"content": "<|unused_26|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100296": {
|
||||||
|
"content": "<|unused_27|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100297": {
|
||||||
|
"content": "<|unused_28|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100298": {
|
||||||
|
"content": "<|unused_29|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100299": {
|
||||||
|
"content": "<|unused_30|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100300": {
|
||||||
|
"content": "<|unused_31|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100301": {
|
||||||
|
"content": "<|unused_32|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100302": {
|
||||||
|
"content": "<|unused_33|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100303": {
|
||||||
|
"content": "<|unused_34|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100304": {
|
||||||
|
"content": "<|unused_35|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100305": {
|
||||||
|
"content": "<|unused_36|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100306": {
|
||||||
|
"content": "<|unused_37|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100307": {
|
||||||
|
"content": "<|unused_38|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100308": {
|
||||||
|
"content": "<|unused_39|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100309": {
|
||||||
|
"content": "<|unused_40|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100310": {
|
||||||
|
"content": "<|unused_41|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100311": {
|
||||||
|
"content": "<|unused_42|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100312": {
|
||||||
|
"content": "<|unused_43|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100313": {
|
||||||
|
"content": "<|unused_44|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100314": {
|
||||||
|
"content": "<|unused_45|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100315": {
|
||||||
|
"content": "<|unused_46|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100316": {
|
||||||
|
"content": "<|unused_47|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100317": {
|
||||||
|
"content": "<|unused_48|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100318": {
|
||||||
|
"content": "<|unused_49|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100319": {
|
||||||
|
"content": "<|unused_50|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100320": {
|
||||||
|
"content": "<|unused_51|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100321": {
|
||||||
|
"content": "<|unused_52|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100322": {
|
||||||
|
"content": "<|unused_53|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100323": {
|
||||||
|
"content": "<|unused_54|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100324": {
|
||||||
|
"content": "<|unused_55|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100325": {
|
||||||
|
"content": "<|unused_56|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100326": {
|
||||||
|
"content": "<|unused_57|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100327": {
|
||||||
|
"content": "<|unused_58|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100328": {
|
||||||
|
"content": "<|unused_59|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100329": {
|
||||||
|
"content": "<|unused_60|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100330": {
|
||||||
|
"content": "<|unused_61|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100331": {
|
||||||
|
"content": "<|unused_62|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100332": {
|
||||||
|
"content": "<|unused_63|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100333": {
|
||||||
|
"content": "<|unused_64|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100334": {
|
||||||
|
"content": "<|unused_65|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100335": {
|
||||||
|
"content": "<|unused_66|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100336": {
|
||||||
|
"content": "<|unused_67|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100337": {
|
||||||
|
"content": "<|unused_68|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100338": {
|
||||||
|
"content": "<|unused_69|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100339": {
|
||||||
|
"content": "<|unused_70|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100340": {
|
||||||
|
"content": "<|unused_71|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100341": {
|
||||||
|
"content": "<|unused_72|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100342": {
|
||||||
|
"content": "<|unused_73|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100343": {
|
||||||
|
"content": "<|unused_74|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100344": {
|
||||||
|
"content": "<|unused_75|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100345": {
|
||||||
|
"content": "<|unused_76|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100346": {
|
||||||
|
"content": "<|unused_77|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100347": {
|
||||||
|
"content": "<|unused_78|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100348": {
|
||||||
|
"content": "<|unused_79|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100349": {
|
||||||
|
"content": "<|unused_80|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100350": {
|
||||||
|
"content": "<|unused_81|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"100351": {
|
||||||
|
"content": "<|unused_82|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"bos_token": "<|end_of_text|>",
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|end_of_text|>",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"model_max_length": 1000000000000000019884624838656,
|
||||||
|
"pad_token": "<|pad|>",
|
||||||
|
"padding_side": "left",
|
||||||
|
"tokenizer_class": "GPT2Tokenizer",
|
||||||
|
"unk_token": "<|unk|>"
|
||||||
|
}
|
||||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user