初始化项目，由ModelHub XC社区提供模型
Model: DiTy/gemma-2-9b-it-russian-function-calling-GGUF Source: Original Platform
This commit is contained in:
ModelHub XC
41
.gitattributes
vendored
Normal file
41
.gitattributes
vendored
Normal file
@@ -0,0 +1,41 @@
|
||||
*.7z filter=lfs diff=lfs merge=lfs -text
|
||||
*.arrow filter=lfs diff=lfs merge=lfs -text
|
||||
*.bin filter=lfs diff=lfs merge=lfs -text
|
||||
*.bz2 filter=lfs diff=lfs merge=lfs -text
|
||||
*.ckpt filter=lfs diff=lfs merge=lfs -text
|
||||
*.ftz filter=lfs diff=lfs merge=lfs -text
|
||||
*.gz filter=lfs diff=lfs merge=lfs -text
|
||||
*.h5 filter=lfs diff=lfs merge=lfs -text
|
||||
*.joblib filter=lfs diff=lfs merge=lfs -text
|
||||
*.lfs.* filter=lfs diff=lfs merge=lfs -text
|
||||
*.mlmodel filter=lfs diff=lfs merge=lfs -text
|
||||
*.model filter=lfs diff=lfs merge=lfs -text
|
||||
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
||||
*.npy filter=lfs diff=lfs merge=lfs -text
|
||||
*.npz filter=lfs diff=lfs merge=lfs -text
|
||||
*.onnx filter=lfs diff=lfs merge=lfs -text
|
||||
*.ot filter=lfs diff=lfs merge=lfs -text
|
||||
*.parquet filter=lfs diff=lfs merge=lfs -text
|
||||
*.pb filter=lfs diff=lfs merge=lfs -text
|
||||
*.pickle filter=lfs diff=lfs merge=lfs -text
|
||||
*.pkl filter=lfs diff=lfs merge=lfs -text
|
||||
*.pt filter=lfs diff=lfs merge=lfs -text
|
||||
*.pth filter=lfs diff=lfs merge=lfs -text
|
||||
*.rar filter=lfs diff=lfs merge=lfs -text
|
||||
*.safetensors filter=lfs diff=lfs merge=lfs -text
|
||||
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
||||
*.tar.* filter=lfs diff=lfs merge=lfs -text
|
||||
*.tar filter=lfs diff=lfs merge=lfs -text
|
||||
*.tflite filter=lfs diff=lfs merge=lfs -text
|
||||
*.tgz filter=lfs diff=lfs merge=lfs -text
|
||||
*.wasm filter=lfs diff=lfs merge=lfs -text
|
||||
*.xz filter=lfs diff=lfs merge=lfs -text
|
||||
*.zip filter=lfs diff=lfs merge=lfs -text
|
||||
*.zst filter=lfs diff=lfs merge=lfs -text
|
||||
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
||||
tokenizer.json filter=lfs diff=lfs merge=lfs -text
|
||||
gemma-2-9B-it-russian-function-calling-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
|
||||
gemma-2-9B-it-russian-function-calling-F16.gguf filter=lfs diff=lfs merge=lfs -text
|
||||
gemma-2-9B-it-russian-function-calling-Q6_k.gguf filter=lfs diff=lfs merge=lfs -text
|
||||
gemma-2-9B-it-russian-function-calling-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
|
||||
gemma-2-9B-it-russian-function-calling-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
|
||||
408
README.md
Normal file
408
README.md
Normal file
@@ -0,0 +1,408 @@
|
||||
---
|
||||
base_model: google/gemma-2-9b-it
|
||||
datasets:
|
||||
- DiTy/function-calling
|
||||
language:
|
||||
- ru
|
||||
library_name: transformers
|
||||
license: apache-2.0
|
||||
pipeline_tag: text-generation
|
||||
tags:
|
||||
- conversational
|
||||
- gemma2
|
||||
- function-calling
|
||||
- trl
|
||||
---
|
||||
# DiTy/gemma-2-9b-it-russian-function-calling-GGUF
|
||||
|
||||
This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) for the **Function Calling** task on non-synthetic data,
|
||||
fully annotated by humans only, on the Russian version of the <ins>*DiTy/function-calling*</ins> dataset.
|
||||
<!-- Provide a quick summary of what the model is/does. -->
|
||||
|
||||
In addition to **safetensors**, the model is available in **GGUF** formats (in this case, you need to download only a single file (*[how to inference GGUF model](https://github.com/abetlen/llama-cpp-python?tab=readme-ov-file#high-level-api)*)):
|
||||
|
||||
| Filename | Quant type | File Size | Description |
|
||||
| -------- | ---------- | --------- | ----------- |
|
||||
| [gemma-2-9B-it-russian-function-calling-F16.gguf](https://huggingface.co/DiTy/gemma-2-9b-it-russian-function-calling-GGUF/blob/main/gemma-2-9B-it-russian-function-calling-F16.gguf) | F16 | 18.5GB | Base model with float16 |
|
||||
|
||||
|
||||
## Model card разделы
|
||||
|
||||
* [Как подготовить ваши функции (tools) для *Function Calling*](#prepare_func_call)
|
||||
* [Просто используйте chat template для генерации](#just_chat_template)
|
||||
* [Prompt структура и ожидаемый контент](#roles)
|
||||
* [Оценка моделей под вызов функций](#eval)
|
||||
|
||||
## Использование (HuggingFace Transformers)
|
||||
|
||||
Ниже представлены некоторые фрагменты кода о том, как быстро приступить к запуску модели. Сначала установите библиотеку Transformers с помощью:
|
||||
```bash
|
||||
pip install -U transformers
|
||||
```
|
||||
|
||||
### <a name="prepare_func_call"></a>Как подготовить ваши функции (tools) для *Function Calling*
|
||||
|
||||
Вы должны написать функции (инструменты), используемые моделью, в *коде на Python* и обязательно добавить *Python docstrings*, как в примере ниже:
|
||||
```python
|
||||
def get_weather(city: str):
|
||||
"""
|
||||
Функция, которая возвращает погоду в заданном городе.
|
||||
|
||||
Args:
|
||||
city: Город, для которого надо узнать погоду.
|
||||
"""
|
||||
import random
|
||||
|
||||
return "sunny" if random.random() > 0.5 else "rainy"
|
||||
|
||||
|
||||
def get_sunrise_sunset_times(city: str):
|
||||
"""
|
||||
Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].
|
||||
|
||||
Args:
|
||||
city: Город, в котором можно узнать время восхода и захода солнца.
|
||||
"""
|
||||
|
||||
return ["6:00", "18:00"]
|
||||
```
|
||||
|
||||
### <a name="just_chat_template"></a>Просто используйте chat template для генерации
|
||||
|
||||
Далее вам нужно загрузить модель и токенизатор:
|
||||
```python
|
||||
import torch
|
||||
from transformers import AutoTokenizer, AutoModelForCausalLM
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
"DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
|
||||
device_map="auto",
|
||||
torch_dtype=torch.bfloat16, # use float16 or float32 if bfloat16 is not available to you.
|
||||
cache_dir=PATH_TO_MODEL_DIR, # optional
|
||||
)
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
|
||||
cache_dir=PATH_TO_MODEL_DIR, # optional
|
||||
)
|
||||
```
|
||||
|
||||
Чтобы получить результат генерации, просто используйте `apply_chat_template`. Чтобы учесть наши написанные функции (инструменты),
|
||||
нам нужно передать их в виде списка через атрибут `tools`, а также использовать `add_prompt_generation=True`.
|
||||
```python
|
||||
history_messages = [
|
||||
{"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
|
||||
{"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"}
|
||||
]
|
||||
inputs = tokenizer.apply_chat_template(
|
||||
history_messages,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True, # adding prompt for generation
|
||||
tools=[get_weather, get_sunrise_sunset_times], # our functions (tools)
|
||||
)
|
||||
print(inputs)
|
||||
```
|
||||
|
||||
Тогда наш `inputs` будет выглядеть следующим образом:
|
||||
```
|
||||
<bos><start_of_turn>user
|
||||
Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
|
||||
"name": "get_weather",
|
||||
"description": "Функция, которая возвращает погоду в заданном городе.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, для которого надо узнать погоду."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"name": "get_sunrise_sunset_times",
|
||||
"description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, в котором можно узнать время восхода и захода солнца."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
|
||||
<start_of_turn>model
|
||||
```
|
||||
|
||||
Теперь мы можем сгенерировать ответ модели.
|
||||
Будьте осторожны, потому что после `apply_chat_template` нет необходимости *добавлять специальные токены* во время токенизации.
|
||||
Поэтому используем `add_special_tokens=False`:
|
||||
```python
|
||||
terminator_ids = [
|
||||
tokenizer.eos_token_id,
|
||||
tokenizer.convert_tokens_to_ids("<end_of_turn>"),
|
||||
]
|
||||
prompt_ids = tokenizer.encode(inputs, add_special_tokens=False, return_tensors='pt').to(model.device)
|
||||
generated_ids = model.generate(
|
||||
prompt_ids,
|
||||
max_new_tokens=512,
|
||||
eos_token_id=terminator_ids,
|
||||
bos_token_id=tokenizer.bos_token_id,
|
||||
)
|
||||
generated_response = tokenizer.decode(generated_ids[0][prompt_ids.shape[-1]:], skip_special_tokens=False) # `skip_special_tokens=False` for debug
|
||||
print(generated_response)
|
||||
```
|
||||
|
||||
Мы получаем генерацию в виде вызова функции:
|
||||
```
|
||||
Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
|
||||
```
|
||||
|
||||
Отлично, теперь мы можем получать и обрабатывать результаты с помощью нашей *вызываемой функции*, а затем предоставлять модели ответ *функции*:
|
||||
```python
|
||||
history_messages = [
|
||||
{"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
|
||||
{"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
|
||||
{"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Los Angeles"}}'},
|
||||
{"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'}, # гипотетический ответ от нашей функции
|
||||
]
|
||||
inputs = tokenizer.apply_chat_template(
|
||||
history_messages,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True, # добавление запроса для генерации
|
||||
tools=[get_weather, get_sunrise_sunset_times], # наши функции (tools)
|
||||
)
|
||||
print(inputs)
|
||||
```
|
||||
|
||||
Давайте убедимся, что `inputs` верны:
|
||||
```
|
||||
<bos><start_of_turn>user
|
||||
Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
|
||||
"name": "get_weather",
|
||||
"description": "Функция, которая возвращает погоду в заданном городе.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, для которого надо узнать погоду."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"name": "get_sunrise_sunset_times",
|
||||
"description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, в котором можно узнать время восхода и захода солнца."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
|
||||
<start_of_turn>model
|
||||
Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
|
||||
<start_of_turn>user
|
||||
Ответ от функции: {"times_list": ["6:00", "18:00"]}<end_of_turn>
|
||||
<start_of_turn>model
|
||||
```
|
||||
|
||||
Аналогично, мы генерируем ответ модели:
|
||||
```python
|
||||
prompt_ids = tokenizer.encode(inputs, add_special_tokens=False, return_tensors='pt').to(model.device)
|
||||
generated_ids = model.generate(
|
||||
prompt_ids,
|
||||
max_new_tokens=512,
|
||||
eos_token_id=terminator_ids,
|
||||
bos_token_id=tokenizer.bos_token_id,
|
||||
)
|
||||
generated_response = tokenizer.decode(generated_ids[0][prompt_ids.shape[-1]:], skip_special_tokens=False) # `skip_special_tokens=False` for debug
|
||||
print(generated_response)
|
||||
```
|
||||
|
||||
В результате мы получаем ответ модели:
|
||||
```
|
||||
В Краснодаре солнце восходит в 6:00 утра и заходит в 18:00 вечера.<end_of_turn>
|
||||
```
|
||||
|
||||
## Использование через transformers `pipeline`
|
||||
|
||||
<details>
|
||||
<summary>
|
||||
Generation via pipeline
|
||||
</summary>
|
||||
|
||||
```python
|
||||
from transformers import pipeline
|
||||
generation_pipeline = pipeline(
|
||||
"text-generation",
|
||||
model="DiTy/gemma-2-9b-it-russian-function-calling-GGUF",
|
||||
model_kwargs={
|
||||
"torch_dtype": torch.bfloat16, # use float16 or float32 if bfloat16 is not supported for you.
|
||||
"cache_dir": PATH_TO_MODEL_DIR, # OPTIONAL
|
||||
},
|
||||
device_map="auto",
|
||||
)
|
||||
history_messages = [
|
||||
{"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
|
||||
{"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
|
||||
{"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}'},
|
||||
{"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'}
|
||||
]
|
||||
inputs = generation_pipeline.tokenizer.apply_chat_template(
|
||||
history_messages,
|
||||
tokenize=False,
|
||||
add_generation_prompt=True,
|
||||
tools=[get_weather, get_sunrise_sunset_times],
|
||||
)
|
||||
terminator_ids = [
|
||||
generation_pipeline.tokenizer.eos_token_id,
|
||||
generation_pipeline.tokenizer.convert_tokens_to_ids("<end_of_turn>")
|
||||
]
|
||||
outputs = generation_pipeline(
|
||||
inputs,
|
||||
max_new_tokens=512,
|
||||
eos_token_id=terminator_ids,
|
||||
)
|
||||
print(outputs[0]["generated_text"][len(inputs):])
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
## <a name="roles"></a>Prompt структура и ожидаемый контент
|
||||
|
||||
Для наиболее корректной работы модели предполагается, что будет использоваться `apply_chat_template`.
|
||||
Необходимо передать историю сообщений в определенном формате.
|
||||
```python
|
||||
history_messages = [
|
||||
{"role": "...", "content": "..."},
|
||||
...
|
||||
]
|
||||
```
|
||||
|
||||
Для использования доступны следующие роли:
|
||||
|
||||
* `system` - это необязательная роль, ее содержимое всегда размещается в самом начале и перед перечислением функций, доступных модели (инструментов).
|
||||
Вы всегда можете воспользоваться стандартным вариантом, который использовался во время обучения: ***"Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "***
|
||||
* `user` - запрос пользователя передается через эту роль.
|
||||
* `function-call` - тело вызова функции передается через эту роль.
|
||||
Хотя модель обучена генерировать вызов функции в виде ***"Вызов функции: {...}\<end_of_turn\>"***, вы все равно должны передать только тело ***"{...}"***
|
||||
в поле *"content"*, поскольку используя `apply_chat_template`, постскриптум в инструкциях добавляется автоматически.
|
||||
* `function-response` - в этой роли мы должны передать ответ нашей функции в поле *"content"* в виде словаря ***'{"name_returnable_value": value}'***.
|
||||
* `model` - содержимое, относящееся к этой роли, считается сгенерированным текстом модели.
|
||||
|
||||
|
||||
### Структура истории чата для *Function Calling*
|
||||
|
||||
```
|
||||
[
|
||||
{"role": "system", "content": "Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - "},
|
||||
{"role": "user", "content": "Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?"},
|
||||
{"role": "function-call", "content": '{"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}'},
|
||||
{"role": "function-response", "content": '{"times_list": ["6:00", "18:00"]}'}
|
||||
]
|
||||
```
|
||||
|
||||
Это выглядит как:
|
||||
```
|
||||
<bos><start_of_turn>user
|
||||
Ты - полезный помощник, имеющий доступ к следующим функциям. Используйте их при необходимости - {
|
||||
"name": "get_weather",
|
||||
"description": "Функция, которая возвращает погоду в заданном городе.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, для которого надо узнать погоду."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
},
|
||||
{
|
||||
"name": "get_sunrise_sunset_times",
|
||||
"description": "Функция, которая возвращает время восхода и заката для заданного города для текущей даты (дата от пользователя не требуется), в формате списка: [sunrise_time, sunset_time].",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"city": {
|
||||
"type": "string",
|
||||
"description": "Город, в котором можно узнать время восхода и захода солнца."
|
||||
}
|
||||
},
|
||||
"required": [
|
||||
"city"
|
||||
]
|
||||
}
|
||||
}
|
||||
|
||||
Привет, не мог бы ты сказать мне, во сколько в Краснодаре восходит солнце?<end_of_turn>
|
||||
<start_of_turn>model
|
||||
Вызов функции: {"name": "get_sunrise_sunset_times", "arguments": {"city": "Краснодар"}}<end_of_turn>
|
||||
<start_of_turn>user
|
||||
Ответ от функции: {"times_list": ["6:00", "18:00"]}<end_of_turn>
|
||||
```
|
||||
|
||||
|
||||
### Структура истории чата для обычного user-model шаблона
|
||||
|
||||
```
|
||||
[
|
||||
{"role": "system", "content": "Ты добрый помощник"},
|
||||
{"role": "user", "content": "Расскажи мне о Москве"}
|
||||
]
|
||||
```
|
||||
|
||||
Это выглядит как:
|
||||
```
|
||||
<bos><start_of_turn>user
|
||||
Ты добрый помощник
|
||||
|
||||
Расскажи мне о Москве<end_of_turn>
|
||||
```
|
||||
|
||||
## <a name="eval"></a>Оценка моделей
|
||||
|
||||
В процессе обучения ошибка валидации была приближена к следующим значениям:
|
||||
|
||||
| **Model** | **Generation Language** | **Approximately Validation Loss** |
|
||||
| :-----: | :-----: | :-----: |
|
||||
| [DiTy/gemma-2-27b-it-function-calling-GGUF](https://huggingface.co/DiTy/gemma-2-27b-it-function-calling-GGUF) | EN | 0.47 |
|
||||
| [**DiTy/gemma-2-9b-it-russian-function-calling-GGUF**](https://huggingface.co/DiTy/gemma-2-9b-it-russian-function-calling-GGUF) | **RU** | **0.57** |
|
||||
| [DiTy/gemma-2-9b-it-function-calling-GGUF](https://huggingface.co/DiTy/gemma-2-9b-it-function-calling-GGUF) | EN | 0.5 |
|
||||
| [DiTy/gemma-2-2b-it-function-calling](https://huggingface.co/DiTy/gemma-2-2b-it-function-calling) | EN | 0.66 |
|
||||
|
||||
## Citation
|
||||
|
||||
```none
|
||||
@article{gemma_2024,
|
||||
title={Gemma},
|
||||
url={https://www.kaggle.com/m/3301},
|
||||
DOI={10.34740/KAGGLE/M/3301},
|
||||
publisher={Kaggle},
|
||||
author={Gemma Team},
|
||||
year={2024}
|
||||
}
|
||||
```
|
||||
34
config.json
Normal file
34
config.json
Normal file
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"_name_or_path": "google/gemma-2-9b-it",
|
||||
"architectures": [
|
||||
"Gemma2ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"attn_logit_softcapping": 50.0,
|
||||
"bos_token_id": 2,
|
||||
"cache_implementation": "hybrid",
|
||||
"eos_token_id": 1,
|
||||
"final_logit_softcapping": 30.0,
|
||||
"head_dim": 256,
|
||||
"hidden_act": "gelu_pytorch_tanh",
|
||||
"hidden_activation": "gelu_pytorch_tanh",
|
||||
"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 14336,
|
||||
"max_position_embeddings": 8192,
|
||||
"model_type": "gemma2",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 42,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 0,
|
||||
"query_pre_attn_scalar": 256,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_theta": 10000.0,
|
||||
"sliding_window": 4096,
|
||||
"sliding_window_size": 4096,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.42.2",
|
||||
"use_cache": true,
|
||||
"vocab_size": 256000
|
||||
}
|
||||
3
gemma-2-9B-it-russian-function-calling-F16.gguf
Normal file
3
gemma-2-9B-it-russian-function-calling-F16.gguf
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:423b74a954d90ecab4cd25cd832eb8aea795a852a3ef464967ac8bf5865e13e7
|
||||
size 18490683264
|
||||
8
generation_config.json
Normal file
8
generation_config.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 2,
|
||||
"cache_implementation": "hybrid",
|
||||
"eos_token_id": 1,
|
||||
"pad_token_id": 0,
|
||||
"transformers_version": "4.42.2"
|
||||
}
|
||||
3
model-00001-of-00004.safetensors
Normal file
3
model-00001-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:318e44237d2d9fa0f55cc1c26c89fa770e2066cc2875db74af20420315c2fbc5
|
||||
size 4903351912
|
||||
3
model-00002-of-00004.safetensors
Normal file
3
model-00002-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:1f9c305ce9d0588ac22c71f663cfd3c2ed6f4c64012d5244b12bf5bc5d60fdff
|
||||
size 4947570872
|
||||
3
model-00003-of-00004.safetensors
Normal file
3
model-00003-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3cad3352d923c487441ae3b7579623cdad22d365576d1d93f1f5c602ef7916fc
|
||||
size 4962221464
|
||||
3
model-00004-of-00004.safetensors
Normal file
3
model-00004-of-00004.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:48752a998e4ec33707d3d576de9d19e0f0a73fd54837686245739f455b46ebe1
|
||||
size 3670322200
|
||||
471
model.safetensors.index.json
Normal file
471
model.safetensors.index.json
Normal file
@@ -0,0 +1,471 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 18483411968
|
||||
},
|
||||
"weight_map": {
|
||||
"model.embed_tokens.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.18.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.21.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.22.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.28.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.29.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.30.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.30.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.input_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.post_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.pre_feedforward_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.31.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.32.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.32.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.32.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.32.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.32.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.32.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.33.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.33.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.34.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.35.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.36.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.37.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.38.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.39.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.40.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.40.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.input_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.post_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.pre_feedforward_layernorm.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.41.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
|
||||
"model.layers.5.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.post_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.pre_feedforward_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.7.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.7.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.7.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.7.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.pre_feedforward_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.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
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:3f289bc05132635a8bc7aca7aa21255efd5e18f3710f43e3cdb96bcd41be4922
|
||||
size 17525357
|
||||
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
|
||||
2013
tokenizer_config.json
Normal file
2013
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user