初始化项目，由ModelHub XC社区提供模型
Model: Josephgflowers/Cinder-Phi-2-V1-F16-gguf Source: Original Platform
This commit is contained in:
ModelHub XC
49
.gitattributes
vendored
Normal file
49
.gitattributes
vendored
Normal file
@@ -0,0 +1,49 @@
|
||||
*.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
|
||||
*.pt2 filter=lfs diff=lfs merge=lfs -text
|
||||
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||
|
||||
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
||||
3
Cinder-Phi-2-V1.F16.gguf
Normal file
3
Cinder-Phi-2-V1.F16.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d4a53a616e77025ad8ec9f725046910ec397c446eb64ff9edbb453e705ffb82a
|
||||
size 5563095616
|
||||
248
README.md
Normal file
248
README.md
Normal file
@@ -0,0 +1,248 @@
|
||||
---
|
||||
license: mit
|
||||
widget:
|
||||
- text: '<|system|>
|
||||
|
||||
You are a helpful assistant.</s>
|
||||
|
||||
<|user|>
|
||||
|
||||
Can you explain to me how quantum computing works?</s>
|
||||
|
||||
<|assistant|>
|
||||
|
||||
'
|
||||
model-index:
|
||||
- name: Cinder-Phi-2-V1-F16-gguf
|
||||
results:
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: AI2 Reasoning Challenge (25-Shot)
|
||||
type: ai2_arc
|
||||
config: ARC-Challenge
|
||||
split: test
|
||||
args:
|
||||
num_few_shot: 25
|
||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 58.28
|
||||
name: normalized accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: HellaSwag (10-Shot)
|
||||
type: hellaswag
|
||||
split: validation
|
||||
args:
|
||||
num_few_shot: 10
|
||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 74.04
|
||||
name: normalized accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: MMLU (5-Shot)
|
||||
type: cais/mmlu
|
||||
config: all
|
||||
split: test
|
||||
args:
|
||||
num_few_shot: 5
|
||||
metrics:
|
||||
- type: acc
|
||||
value: 54.46
|
||||
name: accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: TruthfulQA (0-shot)
|
||||
type: truthful_qa
|
||||
config: multiple_choice
|
||||
split: validation
|
||||
args:
|
||||
num_few_shot: 0
|
||||
metrics:
|
||||
- type: mc2
|
||||
value: 44.5
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: Winogrande (5-shot)
|
||||
type: winogrande
|
||||
config: winogrande_xl
|
||||
split: validation
|
||||
args:
|
||||
num_few_shot: 5
|
||||
metrics:
|
||||
- type: acc
|
||||
value: 74.66
|
||||
name: accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: GSM8k (5-shot)
|
||||
type: gsm8k
|
||||
config: main
|
||||
split: test
|
||||
args:
|
||||
num_few_shot: 5
|
||||
metrics:
|
||||
- type: acc
|
||||
value: 47.23
|
||||
name: accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: IFEval (0-Shot)
|
||||
type: HuggingFaceH4/ifeval
|
||||
args:
|
||||
num_few_shot: 0
|
||||
metrics:
|
||||
- type: inst_level_strict_acc and prompt_level_strict_acc
|
||||
value: 23.57
|
||||
name: strict accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: BBH (3-Shot)
|
||||
type: BBH
|
||||
args:
|
||||
num_few_shot: 3
|
||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 22.45
|
||||
name: normalized accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: MATH Lvl 5 (4-Shot)
|
||||
type: hendrycks/competition_math
|
||||
args:
|
||||
num_few_shot: 4
|
||||
metrics:
|
||||
- type: exact_match
|
||||
value: 0.0
|
||||
name: exact match
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: GPQA (0-shot)
|
||||
type: Idavidrein/gpqa
|
||||
args:
|
||||
num_few_shot: 0
|
||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 4.25
|
||||
name: acc_norm
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: MuSR (0-shot)
|
||||
type: TAUR-Lab/MuSR
|
||||
args:
|
||||
num_few_shot: 0
|
||||
metrics:
|
||||
- type: acc_norm
|
||||
value: 1.97
|
||||
name: acc_norm
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
- task:
|
||||
type: text-generation
|
||||
name: Text Generation
|
||||
dataset:
|
||||
name: MMLU-PRO (5-shot)
|
||||
type: TIGER-Lab/MMLU-Pro
|
||||
config: main
|
||||
split: test
|
||||
args:
|
||||
num_few_shot: 5
|
||||
metrics:
|
||||
- type: acc
|
||||
value: 12.9
|
||||
name: accuracy
|
||||
source:
|
||||
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Josephgflowers/Cinder-Phi-2-V1-F16-gguf
|
||||
name: Open LLM Leaderboard
|
||||
---
|
||||
|
||||
I am really enjoying this version of Cinder. More information coming. Training data similar to openhermes2.5 with some added math, STEM, and reasoning mostly from OpenOrca. As well as Cinder character specific data, a mix of RAG generated Q and A of world knowledge, STEM topics, and Cinder Character data. I suplimented the Cinder character with an abreviated Samantha dataset edited for Cinder and removed a lot of the negative responses.
|
||||
Model Overview Cinder is an AI chatbot tailored for engaging users in scientific and educational conversations, offering companionship, and sparking imaginative exploration.
|
||||
|
||||
|
||||
|
||||
|
||||
Chat example from LM Studio:
|
||||
|
||||
|
||||
|
||||
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
|
||||
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Josephgflowers__Cinder-Phi-2-V1-F16-gguf)
|
||||
|
||||
| Metric |Value|
|
||||
|---------------------------------|----:|
|
||||
|Avg. |58.86|
|
||||
|AI2 Reasoning Challenge (25-Shot)|58.28|
|
||||
|HellaSwag (10-Shot) |74.04|
|
||||
|MMLU (5-Shot) |54.46|
|
||||
|TruthfulQA (0-shot) |44.50|
|
||||
|Winogrande (5-shot) |74.66|
|
||||
|GSM8k (5-shot) |47.23|
|
||||
|
||||
|
||||
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
|
||||
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Josephgflowers__Cinder-Phi-2-V1-F16-gguf)
|
||||
|
||||
| Metric |Value|
|
||||
|-------------------|----:|
|
||||
|Avg. |10.86|
|
||||
|IFEval (0-Shot) |23.57|
|
||||
|BBH (3-Shot) |22.45|
|
||||
|MATH Lvl 5 (4-Shot)| 0.00|
|
||||
|GPQA (0-shot) | 4.25|
|
||||
|MuSR (0-shot) | 1.97|
|
||||
|MMLU-PRO (5-shot) |12.90|
|
||||
|
||||
42
added_tokens.json
Normal file
42
added_tokens.json
Normal file
@@ -0,0 +1,42 @@
|
||||
{
|
||||
"\t\t": 50294,
|
||||
"\t\t\t": 50293,
|
||||
"\t\t\t\t": 50292,
|
||||
"\t\t\t\t\t": 50291,
|
||||
"\t\t\t\t\t\t": 50290,
|
||||
"\t\t\t\t\t\t\t": 50289,
|
||||
"\t\t\t\t\t\t\t\t": 50288,
|
||||
"\t\t\t\t\t\t\t\t\t": 50287,
|
||||
" ": 50286,
|
||||
" ": 50285,
|
||||
" ": 50284,
|
||||
" ": 50283,
|
||||
" ": 50282,
|
||||
" ": 50281,
|
||||
" ": 50280,
|
||||
" ": 50279,
|
||||
" ": 50278,
|
||||
" ": 50277,
|
||||
" ": 50276,
|
||||
" ": 50275,
|
||||
" ": 50274,
|
||||
" ": 50273,
|
||||
" ": 50272,
|
||||
" ": 50271,
|
||||
" ": 50270,
|
||||
" ": 50269,
|
||||
" ": 50268,
|
||||
" ": 50267,
|
||||
" ": 50266,
|
||||
" ": 50265,
|
||||
" ": 50264,
|
||||
" ": 50263,
|
||||
" ": 50262,
|
||||
" ": 50261,
|
||||
" ": 50260,
|
||||
" ": 50259,
|
||||
" ": 50258,
|
||||
" ": 50257,
|
||||
"<|im_end|>": 50295,
|
||||
"<|im_start|>": 50296
|
||||
}
|
||||
34
config.json
Normal file
34
config.json
Normal file
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"_name_or_path": "/home/joe/mergekit/merge/2-cinder-phi-merge",
|
||||
"architectures": [
|
||||
"PhiForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"auto_map": {
|
||||
"AutoConfig": "configuration_phi.PhiConfig",
|
||||
"AutoModelForCausalLM": "modeling_phi.PhiForCausalLM"
|
||||
},
|
||||
"bos_token_id": 50256,
|
||||
"embd_pdrop": 0.0,
|
||||
"eos_token_id": 50256,
|
||||
"hidden_act": "gelu_new",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 10240,
|
||||
"layer_norm_eps": 1e-05,
|
||||
"max_position_embeddings": 2048,
|
||||
"model_type": "phi",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 32,
|
||||
"num_key_value_heads": 32,
|
||||
"partial_rotary_factor": 0.4,
|
||||
"qk_layernorm": false,
|
||||
"resid_pdrop": 0.1,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 10000.0,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "float16",
|
||||
"transformers_version": "4.38.0.dev0",
|
||||
"use_cache": true,
|
||||
"vocab_size": 51200
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
193
configuration_phi.py
Normal file
193
configuration_phi.py
Normal file
@@ -0,0 +1,193 @@
|
||||
# coding=utf-8
|
||||
# Copyright 2023 Microsoft and the HuggingFace Inc. team. All rights reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
""" Phi model configuration"""
|
||||
|
||||
|
||||
from transformers.configuration_utils import PretrainedConfig
|
||||
from transformers.utils import logging
|
||||
|
||||
|
||||
logger = logging.get_logger(__name__)
|
||||
|
||||
PHI_PRETRAINED_CONFIG_ARCHIVE_MAP = {
|
||||
"microsoft/phi-2": "https://huggingface.co/microsoft/phi-2/resolve/main/config.json",
|
||||
}
|
||||
|
||||
|
||||
class PhiConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`PhiModel`]. It is used to instantiate an Phi
|
||||
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
|
||||
defaults will yield a similar configuration to that of the Phi
|
||||
[microsoft/phi-1](https://huggingface.co/microsoft/phi-1).
|
||||
|
||||
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
|
||||
documentation from [`PretrainedConfig`] for more information.
|
||||
|
||||
Args:
|
||||
vocab_size (`int`, *optional*, defaults to 51200):
|
||||
Vocabulary size of the Phi model. Defines the number of different tokens that can be represented by the
|
||||
`inputs_ids` passed when calling [`PhiModel`].
|
||||
hidden_size (`int`, *optional*, defaults to 2048):
|
||||
Dimension of the hidden representations.
|
||||
intermediate_size (`int`, *optional*, defaults to 8192):
|
||||
Dimension of the MLP representations.
|
||||
num_hidden_layers (`int`, *optional*, defaults to 24):
|
||||
Number of hidden layers in the Transformer decoder.
|
||||
num_attention_heads (`int`, *optional*, defaults to 32):
|
||||
Number of attention heads for each attention layer in the Transformer decoder.
|
||||
num_key_value_heads (`int`, *optional*):
|
||||
This is the number of key_value heads that should be used to implement Grouped Query Attention. If
|
||||
`num_key_value_heads=num_attention_heads`, the model will use Multi Head Attention (MHA), if
|
||||
`num_key_value_heads=1 the model will use Multi Query Attention (MQA) otherwise GQA is used. When
|
||||
converting a multi-head checkpoint to a GQA checkpoint, each group key and value head should be constructed
|
||||
by meanpooling all the original heads within that group. For more details checkout [this
|
||||
paper](https://arxiv.org/pdf/2305.13245.pdf). If it is not specified, will default to
|
||||
`num_attention_heads`.
|
||||
resid_pdrop (`float`, *optional*, defaults to 0.0):
|
||||
Dropout probability for mlp outputs.
|
||||
embd_pdrop (`int`, *optional*, defaults to 0.0):
|
||||
The dropout ratio for the embeddings.
|
||||
attention_dropout (`float`, *optional*, defaults to 0.0):
|
||||
The dropout ratio after computing the attention scores.
|
||||
hidden_act (`str` or `function`, *optional*, defaults to `"gelu_new"`):
|
||||
The non-linear activation function (function or string) in the decoder.
|
||||
max_position_embeddings (`int`, *optional*, defaults to 2048):
|
||||
The maximum sequence length that this model might ever be used with. Phi-1 and Phi-1.5 supports up to 2048
|
||||
tokens.
|
||||
initializer_range (`float`, *optional*, defaults to 0.02):
|
||||
The standard deviation of the truncated_normal_initializer for initializing all weight matrices.
|
||||
layer_norm_eps (`float`, *optional*, defaults to 1e-05):
|
||||
The epsilon used by the rms normalization layers.
|
||||
use_cache (`bool`, *optional*, defaults to `True`):
|
||||
Whether or not the model should return the last key/values attentions (not used by all models). Only
|
||||
relevant if `config.is_decoder=True`. Whether to tie weight embeddings or not.
|
||||
tie_word_embeddings (`bool`, *optional*, defaults to `False`):
|
||||
Whether to tie weight embeddings
|
||||
rope_theta (`float`, *optional*, defaults to 10000.0):
|
||||
The base period of the RoPE embeddings.
|
||||
rope_scaling (`Dict`, *optional*):
|
||||
Dictionary containing the scaling configuration for the RoPE embeddings. Currently supports two scaling
|
||||
strategies: linear and dynamic. Their scaling factor must be an float greater than 1. The expected format
|
||||
is `{"type": strategy name, "factor": scaling factor}`. When using this flag, don't update
|
||||
`max_position_embeddings` to the expected new maximum. See the following thread for more information on how
|
||||
these scaling strategies behave:
|
||||
https://www.reddit.com/r/LocalPersimmon/comments/14mrgpr/dynamically_scaled_rope_further_increases/. This
|
||||
is an experimental feature, subject to breaking API changes in future versions.
|
||||
partial_rotary_factor (`float`, *optional*, defaults to 0.5):
|
||||
Percentage of the query and keys which will have rotary embedding.
|
||||
qk_layernorm (`bool`, *optional*, defaults to `False`):
|
||||
Whether or not to normalize the Queries and Keys after projecting the hidden states.
|
||||
bos_token_id (`int`, *optional*, defaults to 1):
|
||||
Denotes beginning of sequences token id.
|
||||
eos_token_id (`int`, *optional*, defaults to 2):
|
||||
Denotes end of sequences token id.
|
||||
|
||||
Example:
|
||||
|
||||
```python
|
||||
>>> from transformers import PhiModel, PhiConfig
|
||||
|
||||
>>> # Initializing a Phi-1 style configuration
|
||||
>>> configuration = PhiConfig.from_pretrained("microsoft/phi-1")
|
||||
|
||||
>>> # Initializing a model from the configuration
|
||||
>>> model = PhiModel(configuration)
|
||||
|
||||
>>> # Accessing the model configuration
|
||||
>>> configuration = model.config
|
||||
```"""
|
||||
|
||||
model_type = "phi"
|
||||
keys_to_ignore_at_inference = ["past_key_values"]
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
vocab_size=51200,
|
||||
hidden_size=2048,
|
||||
intermediate_size=8192,
|
||||
num_hidden_layers=24,
|
||||
num_attention_heads=32,
|
||||
num_key_value_heads=None,
|
||||
resid_pdrop=0.0,
|
||||
embd_pdrop=0.0,
|
||||
attention_dropout=0.0,
|
||||
hidden_act="gelu_new",
|
||||
max_position_embeddings=2048,
|
||||
initializer_range=0.02,
|
||||
layer_norm_eps=1e-5,
|
||||
use_cache=True,
|
||||
tie_word_embeddings=False,
|
||||
rope_theta=10000.0,
|
||||
rope_scaling=None,
|
||||
partial_rotary_factor=0.5,
|
||||
qk_layernorm=False,
|
||||
bos_token_id=1,
|
||||
eos_token_id=2,
|
||||
**kwargs,
|
||||
):
|
||||
self.vocab_size = vocab_size
|
||||
self.hidden_size = hidden_size
|
||||
self.intermediate_size = intermediate_size
|
||||
self.num_hidden_layers = num_hidden_layers
|
||||
self.num_attention_heads = num_attention_heads
|
||||
|
||||
if num_key_value_heads is None:
|
||||
num_key_value_heads = num_attention_heads
|
||||
|
||||
self.num_key_value_heads = num_key_value_heads
|
||||
self.resid_pdrop = resid_pdrop
|
||||
self.embd_pdrop = embd_pdrop
|
||||
self.attention_dropout = attention_dropout
|
||||
self.hidden_act = hidden_act
|
||||
self.max_position_embeddings = max_position_embeddings
|
||||
self.initializer_range = initializer_range
|
||||
self.layer_norm_eps = layer_norm_eps
|
||||
self.use_cache = use_cache
|
||||
self.rope_theta = rope_theta
|
||||
self.rope_scaling = rope_scaling
|
||||
self.partial_rotary_factor = partial_rotary_factor
|
||||
self.qk_layernorm = qk_layernorm
|
||||
self._rope_scaling_validation()
|
||||
|
||||
super().__init__(
|
||||
bos_token_id=bos_token_id,
|
||||
eos_token_id=eos_token_id,
|
||||
tie_word_embeddings=tie_word_embeddings,
|
||||
**kwargs,
|
||||
)
|
||||
|
||||
# Copied from transformers.models.llama.configuration_llama.LlamaConfig._rope_scaling_validation
|
||||
def _rope_scaling_validation(self):
|
||||
"""
|
||||
Validate the `rope_scaling` configuration.
|
||||
"""
|
||||
if self.rope_scaling is None:
|
||||
return
|
||||
|
||||
if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
|
||||
raise ValueError(
|
||||
"`rope_scaling` must be a dictionary with with two fields, `type` and `factor`, "
|
||||
f"got {self.rope_scaling}"
|
||||
)
|
||||
rope_scaling_type = self.rope_scaling.get("type", None)
|
||||
rope_scaling_factor = self.rope_scaling.get("factor", None)
|
||||
if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
|
||||
raise ValueError(
|
||||
f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"
|
||||
)
|
||||
if rope_scaling_factor is None or not isinstance(rope_scaling_factor, float) or rope_scaling_factor <= 1.0:
|
||||
raise ValueError(f"`rope_scaling`'s factor field must be a float > 1, got {rope_scaling_factor}")
|
||||
6
generation_config.json
Normal file
6
generation_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 50256,
|
||||
"eos_token_id": 50297,
|
||||
"transformers_version": "4.38.0.dev0"
|
||||
}
|
||||
50001
merges.txt
Normal file
50001
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:e65bf07070586d1ba1a024c32e0557191f8a3366ae10f73676377228e5298659
|
||||
size 4995584424
|
||||
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 sha256:6471cbc1a34dafd11e297d5c00e0a01e15b1feb9522c2b6ba26ae805f83004d7
|
||||
size 563832976
|
||||
460
model.safetensors.index.json
Normal file
460
model.safetensors.index.json
Normal file
@@ -0,0 +1,460 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 5559367680
|
||||
},
|
||||
"weight_map": {
|
||||
"lm_head.bias": "model-00002-of-00002.safetensors",
|
||||
"lm_head.weight": "model-00002-of-00002.safetensors",
|
||||
"model.embed_tokens.weight": "model-00001-of-00002.safetensors",
|
||||
"model.final_layernorm.bias": "model-00002-of-00002.safetensors",
|
||||
"model.final_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.0.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.10.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.11.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.12.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.13.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.14.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.15.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.16.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.17.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.18.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.19.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.20.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.21.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.22.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.23.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.24.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.25.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.26.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.27.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.28.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.v_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.29.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.30.input_layernorm.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.mlp.fc1.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.mlp.fc1.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.mlp.fc2.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.mlp.fc2.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.dense.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.dense.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.q_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.q_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.v_proj.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.30.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.input_layernorm.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.input_layernorm.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.mlp.fc1.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.mlp.fc1.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.mlp.fc2.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.mlp.fc2.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.dense.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.dense.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.k_proj.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.k_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.q_proj.bias": "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.bias": "model-00002-of-00002.safetensors",
|
||||
"model.layers.31.self_attn.v_proj.weight": "model-00002-of-00002.safetensors",
|
||||
"model.layers.4.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.fc1.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.fc1.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.fc2.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.mlp.fc2.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.dense.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.dense.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.bias": "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.bias": "model-00001-of-00002.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00001-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
1369
modeling_phi.py
Normal file
1369
modeling_phi.py
Normal file
File diff suppressed because it is too large
Load Diff
3
optimizer.pt
Normal file
3
optimizer.pt
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:59cca1b08af5ad8590847b7e6a617c653999253eaa8b9c7dae2cb777f0e83c74
|
||||
size 11083554
|
||||
3
rng_state.pth
Normal file
3
rng_state.pth
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:5158c69781c3fcbef16ded6c3d4e194b2517c0135772b1a5282c504a76d29676
|
||||
size 14244
|
||||
3
scheduler.pt
Normal file
3
scheduler.pt
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:903322d05f7d5774cc828cf4ee1e28a684c7a8fcdd8a15ef4e20da169be0c6e5
|
||||
size 1064
|
||||
30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"unk_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1d3b61c4bc21578c33581576238dea3ce3a8e95d74109dd6b364723b2211dc97
|
||||
size 2115299
|
||||
340
tokenizer_config.json
Normal file
340
tokenizer_config.json
Normal file
@@ -0,0 +1,340 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"50256": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"50257": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50258": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50259": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50260": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50261": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50262": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50263": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50264": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50265": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50266": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50267": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50268": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50269": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50270": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50271": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50272": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50273": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50274": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50275": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50276": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50277": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50278": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50279": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50280": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50281": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50282": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50283": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50284": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50285": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50286": {
|
||||
"content": " ",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50287": {
|
||||
"content": "\t\t\t\t\t\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50288": {
|
||||
"content": "\t\t\t\t\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50289": {
|
||||
"content": "\t\t\t\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50290": {
|
||||
"content": "\t\t\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50291": {
|
||||
"content": "\t\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50292": {
|
||||
"content": "\t\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50293": {
|
||||
"content": "\t\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50294": {
|
||||
"content": "\t\t",
|
||||
"lstrip": false,
|
||||
"normalized": true,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"50295": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"50296": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"bos_token": "<|endoftext|>",
|
||||
"clean_up_tokenization_spaces": true,
|
||||
"eos_token": "<|im_end|>",
|
||||
"model_max_length": 2048,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"tokenizer_class": "CodeGenTokenizer",
|
||||
"unk_token": "<|endoftext|>"
|
||||
}
|
||||
141
trainer_state.json
Normal file
141
trainer_state.json
Normal file
@@ -0,0 +1,141 @@
|
||||
{
|
||||
"best_metric": null,
|
||||
"best_model_checkpoint": null,
|
||||
"epoch": 0.30120481927710846,
|
||||
"eval_steps": 500,
|
||||
"global_step": 200,
|
||||
"is_hyper_param_search": false,
|
||||
"is_local_process_zero": true,
|
||||
"is_world_process_zero": true,
|
||||
"log_history": [
|
||||
{
|
||||
"epoch": 0.02,
|
||||
"learning_rate": 4.924698795180723e-05,
|
||||
"loss": 1.305,
|
||||
"step": 10
|
||||
},
|
||||
{
|
||||
"epoch": 0.03,
|
||||
"learning_rate": 4.8493975903614455e-05,
|
||||
"loss": 1.1432,
|
||||
"step": 20
|
||||
},
|
||||
{
|
||||
"epoch": 0.05,
|
||||
"learning_rate": 4.774096385542169e-05,
|
||||
"loss": 1.0734,
|
||||
"step": 30
|
||||
},
|
||||
{
|
||||
"epoch": 0.06,
|
||||
"learning_rate": 4.698795180722892e-05,
|
||||
"loss": 1.0555,
|
||||
"step": 40
|
||||
},
|
||||
{
|
||||
"epoch": 0.08,
|
||||
"learning_rate": 4.6234939759036145e-05,
|
||||
"loss": 1.0151,
|
||||
"step": 50
|
||||
},
|
||||
{
|
||||
"epoch": 0.09,
|
||||
"learning_rate": 4.5481927710843374e-05,
|
||||
"loss": 1.1434,
|
||||
"step": 60
|
||||
},
|
||||
{
|
||||
"epoch": 0.11,
|
||||
"learning_rate": 4.4728915662650604e-05,
|
||||
"loss": 1.0396,
|
||||
"step": 70
|
||||
},
|
||||
{
|
||||
"epoch": 0.12,
|
||||
"learning_rate": 4.3975903614457834e-05,
|
||||
"loss": 1.0922,
|
||||
"step": 80
|
||||
},
|
||||
{
|
||||
"epoch": 0.14,
|
||||
"learning_rate": 4.3222891566265064e-05,
|
||||
"loss": 1.047,
|
||||
"step": 90
|
||||
},
|
||||
{
|
||||
"epoch": 0.15,
|
||||
"learning_rate": 4.2469879518072294e-05,
|
||||
"loss": 1.0364,
|
||||
"step": 100
|
||||
},
|
||||
{
|
||||
"epoch": 0.17,
|
||||
"learning_rate": 4.1716867469879523e-05,
|
||||
"loss": 1.0541,
|
||||
"step": 110
|
||||
},
|
||||
{
|
||||
"epoch": 0.18,
|
||||
"learning_rate": 4.0963855421686746e-05,
|
||||
"loss": 0.9778,
|
||||
"step": 120
|
||||
},
|
||||
{
|
||||
"epoch": 0.2,
|
||||
"learning_rate": 4.0210843373493976e-05,
|
||||
"loss": 1.0168,
|
||||
"step": 130
|
||||
},
|
||||
{
|
||||
"epoch": 0.21,
|
||||
"learning_rate": 3.9457831325301206e-05,
|
||||
"loss": 1.0563,
|
||||
"step": 140
|
||||
},
|
||||
{
|
||||
"epoch": 0.23,
|
||||
"learning_rate": 3.8704819277108436e-05,
|
||||
"loss": 0.9837,
|
||||
"step": 150
|
||||
},
|
||||
{
|
||||
"epoch": 0.24,
|
||||
"learning_rate": 3.7951807228915666e-05,
|
||||
"loss": 0.9251,
|
||||
"step": 160
|
||||
},
|
||||
{
|
||||
"epoch": 0.26,
|
||||
"learning_rate": 3.7198795180722895e-05,
|
||||
"loss": 1.0495,
|
||||
"step": 170
|
||||
},
|
||||
{
|
||||
"epoch": 0.27,
|
||||
"learning_rate": 3.644578313253012e-05,
|
||||
"loss": 1.0544,
|
||||
"step": 180
|
||||
},
|
||||
{
|
||||
"epoch": 0.29,
|
||||
"learning_rate": 3.569277108433735e-05,
|
||||
"loss": 1.0473,
|
||||
"step": 190
|
||||
},
|
||||
{
|
||||
"epoch": 0.3,
|
||||
"learning_rate": 3.4939759036144585e-05,
|
||||
"loss": 0.972,
|
||||
"step": 200
|
||||
}
|
||||
],
|
||||
"logging_steps": 10,
|
||||
"max_steps": 664,
|
||||
"num_input_tokens_seen": 0,
|
||||
"num_train_epochs": 1,
|
||||
"save_steps": 200,
|
||||
"total_flos": 2.7583655706624e+16,
|
||||
"train_batch_size": 1,
|
||||
"trial_name": null,
|
||||
"trial_params": null
|
||||
}
|
||||
3
training_args.bin
Normal file
3
training_args.bin
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1c44b482f21872865d45cb5cad94ce56e8f84029d5e907bc45c52000898e00e0
|
||||
size 4856
|
||||
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