初始化项目，由ModelHub XC社区提供模型
Model: rubraAI/Gemma-1.1-2b-Instruct Source: Original Platform
This commit is contained in:
ModelHub XC
37
.gitattributes
vendored
Normal file
37
.gitattributes
vendored
Normal file
@@ -0,0 +1,37 @@
|
||||
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||
*.bin.* filter=lfs diff=lfs merge=lfs -text
|
||||
*.bz2 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
|
||||
*.model filter=lfs diff=lfs merge=lfs -text
|
||||
*.msgpack 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
|
||||
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||
saved_model/**/* 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
|
||||
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
||||
*.tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||
*.db* filter=lfs diff=lfs merge=lfs -text
|
||||
*.ark* filter=lfs diff=lfs merge=lfs -text
|
||||
**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text
|
||||
**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text
|
||||
**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text
|
||||
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||
*.gguf* filter=lfs diff=lfs merge=lfs -text
|
||||
*.ggml filter=lfs diff=lfs merge=lfs -text
|
||||
*.llamafile* filter=lfs diff=lfs merge=lfs -text
|
||||
294
README.md
Normal file
294
README.md
Normal file
@@ -0,0 +1,294 @@
|
||||
---
|
||||
license: gemma
|
||||
library_name: transformers
|
||||
pipeline_tag: text-generation
|
||||
model-index:
|
||||
- name: Rubra-Meta-Llama-3-8B-Instruct
|
||||
results:
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: MMLU
|
||||
name: MMLU
|
||||
metrics:
|
||||
- type: 5-shot
|
||||
value: 38.85
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: GPQA
|
||||
name: GPQA
|
||||
metrics:
|
||||
- type: 0-shot
|
||||
value: 24.55
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: GSM-8K
|
||||
name: GSM-8K
|
||||
metrics:
|
||||
- type: 8-shot, CoT
|
||||
value: 6.14
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: MATH
|
||||
name: MATH
|
||||
metrics:
|
||||
- type: 4-shot, CoT
|
||||
value: 2.38
|
||||
verified: false
|
||||
- task:
|
||||
type: text-generation
|
||||
dataset:
|
||||
type: MT-bench
|
||||
name: MT-bench
|
||||
metrics:
|
||||
- type: GPT-4 as Judge
|
||||
value: 5.75
|
||||
verified: false
|
||||
tags:
|
||||
- function-calling
|
||||
- tool-calling
|
||||
- agentic
|
||||
- rubra
|
||||
- gemma
|
||||
- conversational
|
||||
language:
|
||||
- en
|
||||
---
|
||||
|
||||
# Gemma-1.1 2B Instruct
|
||||
|
||||
## Model Description
|
||||
Gemma-1.1-2B-IT is the result of post-training on the base model [google/gemma-1.1-2b-it](https://huggingface.co/google/gemma-1.1-2b-it). This model is designed for high performance in various instruction-following tasks and complex interactions, including multi-turn function calling and detailed conversations.
|
||||
|
||||
## Training Data
|
||||
The model underwent additional training on a proprietary dataset encompassing diverse instruction-following, chat, and function calling data. This post-training process enhances the model's ability to integrate tools and manage complex interaction scenarios effectively.
|
||||
|
||||
## How to Use
|
||||
|
||||
To use the model with the Hugging Face `transformers` and the rubra library [rubra-tools](https://github.com/rubra-ai/rubra-tools), follow these steps:
|
||||
|
||||
```
|
||||
pip install rubra_tools torch==2.3.0 transformers accelerate modelscope
|
||||
```
|
||||
|
||||
You also need Node.js and npm installed. Once you do, install the `jsonrepair` package - it's used to fix some rare hallucinations by the model.
|
||||
|
||||
```
|
||||
npm install jsonrepair
|
||||
```
|
||||
|
||||
### 1. Load the Model
|
||||
```python
|
||||
from modelscope import AutoModelForCausalLM, AutoTokenizer
|
||||
import torch
|
||||
from rubra_tools import preprocess_input, postprocess_output
|
||||
|
||||
model_id = "rubraAI/Meta-Llama-3-8B-Instruct"
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_id)
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
model_id,
|
||||
torch_dtype="auto",
|
||||
device_map="auto",
|
||||
)
|
||||
```
|
||||
|
||||
### 2. Define Functions
|
||||
|
||||
Here we use 4 functions for a simple math chaining question:
|
||||
```python
|
||||
functions = [
|
||||
{
|
||||
'type': 'function',
|
||||
'function': {
|
||||
'name': 'addition',
|
||||
'description': "Adds two numbers together",
|
||||
'parameters': {
|
||||
'type': 'object',
|
||||
'properties': {
|
||||
'a': {
|
||||
'description': 'First number to add',
|
||||
'type': 'string'
|
||||
},
|
||||
'b': {
|
||||
'description': 'Second number to add',
|
||||
'type': 'string'
|
||||
}
|
||||
},
|
||||
'required': []
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
'type': 'function',
|
||||
'function': {
|
||||
'name': 'subtraction',
|
||||
'description': "Subtracts two numbers",
|
||||
'parameters': {
|
||||
'type': 'object',
|
||||
'properties': {
|
||||
'a': {
|
||||
'description': 'First number to be subtracted from',
|
||||
'type': 'string'
|
||||
},
|
||||
'b': {
|
||||
'description': 'Number to subtract',
|
||||
'type': 'string'
|
||||
}
|
||||
},
|
||||
'required': []
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
'type': 'function',
|
||||
'function': {
|
||||
'name': 'multiplication',
|
||||
'description': "Multiply two numbers together",
|
||||
'parameters': {
|
||||
'type': 'object',
|
||||
'properties': {
|
||||
'a': {
|
||||
'description': 'First number to multiply',
|
||||
'type': 'string'
|
||||
},
|
||||
'b': {
|
||||
'description': 'Second number to multiply',
|
||||
'type': 'string'
|
||||
}
|
||||
},
|
||||
'required': []
|
||||
}
|
||||
}
|
||||
},
|
||||
{
|
||||
'type': 'function',
|
||||
'function': {
|
||||
'name': 'division',
|
||||
'description': "Divide two numbers",
|
||||
'parameters': {
|
||||
'type': 'object',
|
||||
'properties': {
|
||||
'a': {
|
||||
'description': 'First number to use as the dividend',
|
||||
'type': 'string'
|
||||
},
|
||||
'b': {
|
||||
'description': 'Second number to use as the divisor',
|
||||
'type': 'string'
|
||||
}
|
||||
},
|
||||
'required': []
|
||||
}
|
||||
}
|
||||
},
|
||||
]
|
||||
```
|
||||
|
||||
### 3. Start the conversation
|
||||
```python
|
||||
messages = [
|
||||
{"role": "system", "content": "You are a helpful assistant."},
|
||||
{"role": "user", "content": "What is the result of four plus six? Take the result and add 2? Then multiply by 5 and then divide by two"},
|
||||
]
|
||||
|
||||
def run_model(messages, functions):
|
||||
## Format messages in Rubra's format
|
||||
formatted_msgs = preprocess_input(msgs=messages, tools=functions)
|
||||
|
||||
text = tokenizer.apply_chat_template(
|
||||
formatted_msgs,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True
|
||||
)
|
||||
model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
|
||||
|
||||
generated_ids = model.generate(
|
||||
model_inputs.input_ids,
|
||||
max_new_tokens=512
|
||||
)
|
||||
generated_ids = [
|
||||
output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
|
||||
]
|
||||
|
||||
response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
|
||||
return response
|
||||
|
||||
raw_output = run_model(messages, functions)
|
||||
# Check if there's a function call
|
||||
function_call = postprocess_output(raw_output)
|
||||
if function_call:
|
||||
print(function_call)
|
||||
else:
|
||||
print(raw_output)
|
||||
```
|
||||
|
||||
You should see this output, which is a function call made by the AI assistant:
|
||||
```
|
||||
[{'id': 'fc65a533', 'function': {'name': 'addition', 'arguments': '{"a": "4", "b": "6"}'}, 'type': 'function'}]
|
||||
```
|
||||
|
||||
### 4. Add Executed Tool Result to Message History & Continue the Conversation
|
||||
|
||||
```python
|
||||
if function_call:
|
||||
# append the assistant tool call msg
|
||||
messages.append({"role": "assistant", "tool_calls": function_call})
|
||||
# append the result of the tool call in openai format, in this case, the value of add 6 to 4 is 10.
|
||||
messages.append({'role': 'tool', 'tool_call_id': function_call[0]["id"], 'name': function_call[0]["function"]["name"], 'content': '10'})
|
||||
raw_output = run_model(messages, functions)
|
||||
# Check if there's a function call
|
||||
function_call = postprocess_output(raw_output)
|
||||
if function_call:
|
||||
print(function_call)
|
||||
else:
|
||||
print(raw_output)
|
||||
```
|
||||
|
||||
The LLM will make another call
|
||||
```
|
||||
[{'id': '2ffc3de4', 'function': {'name': 'addition', 'arguments': '{"a": "10", "b": "2"}'}, 'type': 'function'}]
|
||||
```
|
||||
|
||||
## Framework Versions
|
||||
|
||||
- Transformers 4.41.2
|
||||
- Pytorch 2.3.1+cu121
|
||||
- Datasets 2.19.2
|
||||
- Tokenizers 0.19.1
|
||||
|
||||
## Limitations and Bias
|
||||
|
||||
While the model performs well on a wide range of tasks, it may still produce biased or incorrect outputs. Users should exercise caution and critical judgment when using the model in sensitive or high-stakes applications. The model's outputs are influenced by the data it was trained on, which may contain inherent biases.
|
||||
|
||||
## Ethical Considerations
|
||||
|
||||
Users should ensure that the deployment of this model adheres to ethical guidelines and consider the potential societal impact of the generated text. Misuse of the model for generating harmful or misleading content is strongly discouraged.
|
||||
|
||||
## Acknowledgements
|
||||
|
||||
We would like to thank Google for the model.
|
||||
|
||||
## Contact Information
|
||||
|
||||
For questions or comments about the model, please reach out to [the rubra team](mailto:rubra@acorn.io).
|
||||
|
||||
## Citation
|
||||
|
||||
If you use this work, please cite it as:
|
||||
|
||||
```
|
||||
@misc {rubra_ai_2024,
|
||||
author = { Sanjay Nadhavajhala and Yingbei Tong },
|
||||
title = { Rubra-Gemma-1.1-2B-IT },
|
||||
year = 2024,
|
||||
url = { https://huggingface.co/rubra-ai/gemma-1.1-2b-it },
|
||||
doi = { 10.57967/hf/2647 },
|
||||
publisher = { Hugging Face }
|
||||
}
|
||||
8
all_results.json
Normal file
8
all_results.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"epoch": 0.9999815653930811,
|
||||
"total_flos": 2.1648841527480484e+19,
|
||||
"train_loss": 0.358738521435558,
|
||||
"train_runtime": 99955.0953,
|
||||
"train_samples_per_second": 10.854,
|
||||
"train_steps_per_second": 0.452
|
||||
}
|
||||
28
config.json
Normal file
28
config.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"_name_or_path": "gemma-1.1-2b-it/run1_short_7300",
|
||||
"architectures": [
|
||||
"GemmaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 2,
|
||||
"eos_token_id": 1,
|
||||
"head_dim": 256,
|
||||
"hidden_act": "gelu_pytorch_tanh",
|
||||
"hidden_activation": "gelu_pytorch_tanh",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 16384,
|
||||
"max_position_embeddings": 8192,
|
||||
"model_type": "gemma",
|
||||
"num_attention_heads": 8,
|
||||
"num_hidden_layers": 21,
|
||||
"num_key_value_heads": 1,
|
||||
"pad_token_id": 0,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_theta": 10000.0,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.41.2",
|
||||
"use_cache": false,
|
||||
"vocab_size": 256000
|
||||
}
|
||||
28
configuration.json
Normal file
28
configuration.json
Normal file
@@ -0,0 +1,28 @@
|
||||
{
|
||||
"_name_or_path": "gemma-1.1-2b-it/run1_short_7300",
|
||||
"architectures": [
|
||||
"GemmaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 2,
|
||||
"eos_token_id": 1,
|
||||
"head_dim": 256,
|
||||
"hidden_act": "gelu_pytorch_tanh",
|
||||
"hidden_activation": "gelu_pytorch_tanh",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 16384,
|
||||
"max_position_embeddings": 8192,
|
||||
"model_type": "gemma",
|
||||
"num_attention_heads": 8,
|
||||
"num_hidden_layers": 21,
|
||||
"num_key_value_heads": 1,
|
||||
"pad_token_id": 0,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_theta": 10000.0,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.41.2",
|
||||
"use_cache": false,
|
||||
"vocab_size": 256000
|
||||
}
|
||||
7
generation_config.json
Normal file
7
generation_config.json
Normal file
@@ -0,0 +1,7 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 2,
|
||||
"eos_token_id": 1,
|
||||
"pad_token_id": 0,
|
||||
"transformers_version": "4.41.2"
|
||||
}
|
||||
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 sha256:9ba4d581a3bc72f74fd6c8959f09600c51b880e9fbdea90f0805af79953e7422
|
||||
size 4945240104
|
||||
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 sha256:20d8f5d0327cd828bd57480d9247078a03f51baa7f593f20ec79fc7444b3ea4b
|
||||
size 1388381704
|
||||
198
model.safetensors.index.json
Normal file
198
model.safetensors.index.json
Normal file
@@ -0,0 +1,198 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 6333599744
|
||||
},
|
||||
"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-00002-of-00002.safetensors",
|
||||
"model.layers.15.mlp.down_proj.weight": "model-00002-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-00002-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-00002-of-00002.safetensors",
|
||||
"model.layers.16.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.v_proj.weight": "model-00002-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-00002-of-00002.safetensors",
|
||||
"model.layers.20.mlp.down_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.mlp.gate_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.mlp.up_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.post_attention_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.o_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.q_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.20.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.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"
|
||||
}
|
||||
}
|
||||
34
special_tokens_map.json
Normal file
34
special_tokens_map.json
Normal file
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<start_of_turn>",
|
||||
"<end_of_turn>"
|
||||
],
|
||||
"bos_token": {
|
||||
"content": "<bos>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<eos>",
|
||||
"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
|
||||
}
|
||||
}
|
||||
838658
tokenizer.json
Normal file
838658
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:61a7b147390c64585d6c3543dd6fc636906c9af3865a5548f27f31aee1d4c8e2
|
||||
size 4241003
|
||||
1759
tokenizer_config.json
Normal file
1759
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user