初始化项目，由ModelHub XC社区提供模型
Model: jaring/qwen-medical 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
|
||||
32
.ipynb_checkpoints/config-checkpoint.json
Normal file
32
.ipynb_checkpoints/config-checkpoint.json
Normal file
@@ -0,0 +1,32 @@
|
||||
{
|
||||
"_name_or_path": "/mnt/workspace/models/Qwen/Qwen2.5-7B",
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
|
||||
"max_position_embeddings": 131072,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"pad_token_id": 151654,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.48.3",
|
||||
"unsloth_version": "2025.3.9",
|
||||
"use_cache": true,
|
||||
"use_mrope": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 152064
|
||||
}
|
||||
8
.ipynb_checkpoints/generation_config-checkpoint.json
Normal file
8
.ipynb_checkpoints/generation_config-checkpoint.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"max_length": 131072,
|
||||
"max_new_tokens": 2048,
|
||||
"pad_token_id": 151654,
|
||||
"transformers_version": "4.48.3"
|
||||
}
|
||||
51
README.md
Normal file
51
README.md
Normal file
@@ -0,0 +1,51 @@
|
||||
---
|
||||
frameworks:
|
||||
- Pytorch
|
||||
license: Apache License 2.0
|
||||
tasks:
|
||||
- text-generation
|
||||
|
||||
#model-type:
|
||||
##如 gpt、phi、llama、chatglm、baichuan 等
|
||||
#- gpt
|
||||
|
||||
#domain:
|
||||
##如 nlp、cv、audio、multi-modal
|
||||
#- nlp
|
||||
|
||||
#language:
|
||||
##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
|
||||
#- cn
|
||||
|
||||
#metrics:
|
||||
##如 CIDEr、Blue、ROUGE 等
|
||||
#- CIDEr
|
||||
|
||||
#tags:
|
||||
##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
|
||||
#- pretrained
|
||||
|
||||
#tools:
|
||||
##如 vllm、fastchat、llamacpp、AdaSeq 等
|
||||
#- vllm
|
||||
---
|
||||
### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
|
||||
#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
|
||||
|
||||
SDK下载
|
||||
```bash
|
||||
#安装ModelScope
|
||||
pip install modelscope
|
||||
```
|
||||
```python
|
||||
#SDK模型下载
|
||||
from modelscope import snapshot_download
|
||||
model_dir = snapshot_download('jaring/qwen-medical')
|
||||
```
|
||||
Git下载
|
||||
```
|
||||
#Git模型下载
|
||||
git clone https://www.modelscope.cn/jaring/qwen-medical.git
|
||||
```
|
||||
|
||||
<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
|
||||
24
added_tokens.json
Normal file
24
added_tokens.json
Normal file
@@ -0,0 +1,24 @@
|
||||
{
|
||||
"</tool_call>": 151658,
|
||||
"<tool_call>": 151657,
|
||||
"<|box_end|>": 151649,
|
||||
"<|box_start|>": 151648,
|
||||
"<|endoftext|>": 151643,
|
||||
"<|file_sep|>": 151664,
|
||||
"<|fim_middle|>": 151660,
|
||||
"<|fim_pad|>": 151662,
|
||||
"<|fim_prefix|>": 151659,
|
||||
"<|fim_suffix|>": 151661,
|
||||
"<|im_end|>": 151645,
|
||||
"<|im_start|>": 151644,
|
||||
"<|image_pad|>": 151655,
|
||||
"<|object_ref_end|>": 151647,
|
||||
"<|object_ref_start|>": 151646,
|
||||
"<|quad_end|>": 151651,
|
||||
"<|quad_start|>": 151650,
|
||||
"<|repo_name|>": 151663,
|
||||
"<|video_pad|>": 151656,
|
||||
"<|vision_end|>": 151653,
|
||||
"<|vision_pad|>": 151654,
|
||||
"<|vision_start|>": 151652
|
||||
}
|
||||
85
chat_with_model.py
Normal file
85
chat_with_model.py
Normal file
@@ -0,0 +1,85 @@
|
||||
import os
|
||||
# 设置环境变量禁用 TensorFlow
|
||||
os.environ["USE_TORCH"] = "1"
|
||||
os.environ["USE_TF"] = "0"
|
||||
|
||||
import torch
|
||||
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||
|
||||
def load_model(model_path):
|
||||
"""
|
||||
加载模型和分词器
|
||||
"""
|
||||
print(f"正在从 {model_path} 加载模型...")
|
||||
|
||||
# 检查 CUDA 是否可用
|
||||
if torch.cuda.is_available():
|
||||
device = torch.device("cuda")
|
||||
print("使用 CUDA 后端加速")
|
||||
# 检查 MPS 是否可用
|
||||
elif torch.backends.mps.is_available():
|
||||
device = torch.device("mps")
|
||||
print("使用 MPS 后端加速")
|
||||
else:
|
||||
device = torch.device("cpu")
|
||||
print("CUDA 和 MPS 均不可用，使用 CPU")
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
model_path,
|
||||
torch_dtype=torch.float16,
|
||||
trust_remote_code=True
|
||||
).to(device)
|
||||
|
||||
print("模型加载完成！")
|
||||
return model, tokenizer, device
|
||||
|
||||
def chat_with_model(model, tokenizer, device):
|
||||
"""
|
||||
与模型进行对话
|
||||
"""
|
||||
history = []
|
||||
print("开始对话，输入 'exit' 退出")
|
||||
|
||||
while True:
|
||||
user_input = input("\n用户: ")
|
||||
if user_input.lower() == 'exit':
|
||||
print("对话结束")
|
||||
break
|
||||
|
||||
# 为 Qwen2 模型构建对话格式
|
||||
if not history:
|
||||
messages = [{"role": "user", "content": user_input}]
|
||||
else:
|
||||
messages = []
|
||||
for i, (user_msg, assistant_msg) in enumerate(history):
|
||||
messages.append({"role": "user", "content": user_msg})
|
||||
messages.append({"role": "assistant", "content": assistant_msg})
|
||||
messages.append({"role": "user", "content": user_input})
|
||||
|
||||
# 使用 tokenizer 处理对话
|
||||
inputs = tokenizer.apply_chat_template(
|
||||
messages,
|
||||
return_tensors="pt"
|
||||
).to(device)
|
||||
|
||||
# 生成回复
|
||||
outputs = model.generate(
|
||||
inputs,
|
||||
max_new_tokens=2048,
|
||||
do_sample=True,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
)
|
||||
|
||||
# 解码回复
|
||||
response = tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True)
|
||||
print(f"\n助手: {response}")
|
||||
|
||||
# 更新历史记录
|
||||
history.append((user_input, response))
|
||||
|
||||
if __name__ == "__main__":
|
||||
model_path = "../qwen-medical"
|
||||
model, tokenizer, device = load_model(model_path)
|
||||
chat_with_model(model, tokenizer, device)
|
||||
120
compare_with_base.py
Normal file
120
compare_with_base.py
Normal file
@@ -0,0 +1,120 @@
|
||||
import pandas as pd
|
||||
from tqdm import tqdm
|
||||
import torch
|
||||
import os
|
||||
# 设置环境变量禁用 TensorFlow
|
||||
os.environ["USE_TORCH"] = "1"
|
||||
os.environ["USE_TF"] = "0"
|
||||
|
||||
import torch
|
||||
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||
|
||||
# 设置设备
|
||||
device = torch.device("mps" if torch.backends.mps.is_available() else "cpu")
|
||||
print(f"使用设备: {device}")
|
||||
|
||||
# 基础模型路径
|
||||
base_model_path = "../Qwen2.5-7B-Instruct"
|
||||
# 微调模型路径
|
||||
finetuned_model_path = "../qwen-medical" # 修改为您的微调模型路径
|
||||
|
||||
# 加载基础模型
|
||||
base_tokenizer = AutoTokenizer.from_pretrained(base_model_path, trust_remote_code=True)
|
||||
base_model = AutoModelForCausalLM.from_pretrained(
|
||||
base_model_path,
|
||||
torch_dtype=torch.float16,
|
||||
trust_remote_code=True
|
||||
).to(device)
|
||||
|
||||
# 加载微调后模型
|
||||
finetuned_tokenizer = AutoTokenizer.from_pretrained(finetuned_model_path, trust_remote_code=True)
|
||||
finetuned_model = AutoModelForCausalLM.from_pretrained(
|
||||
finetuned_model_path,
|
||||
torch_dtype=torch.float16,
|
||||
trust_remote_code=True
|
||||
).to(device)
|
||||
print("模型加载完成")
|
||||
|
||||
# 准备评估数据
|
||||
# 创建医疗就诊测试数据
|
||||
eval_dataset = [
|
||||
{
|
||||
"Question": "我最近经常感到胸闷气短，特别是在运动后，这可能是什么问题？",
|
||||
"Answer": "您描述的症状可能与心肺功能有关。建议及时就医检查，进行心电图、胸片等相关检查以明确诊断。同时请注意：1. 暂时减少剧烈运动 2. 保持规律作息 3. 记录症状发生的具体情况"
|
||||
},
|
||||
{
|
||||
"Question": "孩子发烧38.5度，已经持续一天了，除了发烧没有其他明显症状，该怎么处理？",
|
||||
"Answer": "对于儿童发烧，建议以下措施：1. 多补充水分 2. 物理降温（温水擦浴） 3. 必要时使用退烧药 4. 如果发烧持续超过48小时或出现其他症状及时就医 5. 注意观察精神状态和体温变化"
|
||||
},
|
||||
{
|
||||
"Question": "男，十二岁。右股骨下端疼痛2个月，夜间加重。查体：右股骨下端局部肿胀、皮温增高。X线示右胫上端日光射线样改变。首先考虑的诊断是\nA.骨巨细胞瘤 \nB.慢性骨髓炎\nC.股骨结节骨软骨病 \nD.骨样骨瘤 \nE. 骨肉瘤",
|
||||
"Answer": "基于提供的症状和影像学表现，12岁男孩右股骨下端的疼痛具有夜间加重的特点，并伴有局部肿胀和温度升高，X光片显示日光射线样改变，这些都非常符合骨肉瘤的特征。\n\n虽然选项中还有其他可能性，但结合年龄、症状以及特异性的X光表现，最可能的诊断是 E. 骨肉瘤。"
|
||||
},
|
||||
{
|
||||
"Question": "经常性反酸打嗝，体重下降，腹部CT完全正常、肝肾功能正常，癌胚抗原指标正常，这种情况下最可能的诊断是什么",
|
||||
"Answer": "根据提供的症状和检查结果，最可能的诊断是胃食管反流病（GERD）。这种病常见于长期的反酸和打嗝，而CT检查和肝肾功能的正常则排除了其他更严重的疾病。当然，进一步的检查如胃镜可能有助于确诊和排除其他可能性。"
|
||||
},
|
||||
{
|
||||
"Question": "一名中年男性自述鼻涕中带血已经有三个月了，面且伴有有耳堵和听力减退，无发热。根据鼻咽部的症状和体征，这种情况下最可能的诊断是什么？",
|
||||
"Answer": "根据提供的症状以及病程的描述，这名男性患者可能患有鼻咽癌的可能性较高。以下是分析理由：1. **持续时间**：鼻涕中带血已持续三个月，这种情况排除了普通感冒或短期炎症的可能，指向一种更慢性或严重的病变。\n\n2. **症状组合**：鼻涕带血、耳堵及听力减退，这些症状在结合在一起时较为典型地指向鼻咽部的问题。耳堵和听力减退尤其提示可能是由于肿瘤压迫或阻塞了耳咽管。\n\n3. **无发热**：在长期的炎症或感染中，通常会伴随发热现象，而患者并未出现此症状，这降低了急性鼻窦炎等感染的可能性。\n\n鉴于这些症状的组合和其持续的时间，早期鼻咽癌的可能性较高。当然，最终的确诊还需通过影像学检查（如CT或MRI）以及病理活检来确认。不论如何，这种情况下，尽早就医进行详细检查是至关重要的，以便及时获得准确的诊断和适当的治疗。"
|
||||
}
|
||||
]
|
||||
eval_dataset = pd.DataFrame(eval_dataset)
|
||||
test_questions = eval_dataset["Question"].tolist()
|
||||
comparison_results = []
|
||||
|
||||
# 对每个测试样例进行对比评估
|
||||
for question in tqdm(test_questions):
|
||||
# 使用微调模型生成回答
|
||||
formatted_prompt = f"下面列出了一个问题. 请写出问题的答案.### 问题:{question}### 答案:"
|
||||
|
||||
# 微调模型推理
|
||||
finetuned_inputs = finetuned_tokenizer(formatted_prompt, return_tensors="pt").to(device)
|
||||
|
||||
finetuned_outputs = finetuned_model.generate(
|
||||
**finetuned_inputs,
|
||||
max_new_tokens=512,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
do_sample=True
|
||||
)
|
||||
|
||||
finetuned_response = finetuned_tokenizer.decode(finetuned_outputs[0], skip_special_tokens=True)
|
||||
finetuned_response = finetuned_response.replace(formatted_prompt, "") # 移除提示词
|
||||
|
||||
# 基础模型推理
|
||||
base_inputs = base_tokenizer(formatted_prompt, return_tensors="pt").to(device)
|
||||
|
||||
base_outputs = base_model.generate(
|
||||
**base_inputs,
|
||||
max_new_tokens=512,
|
||||
temperature=0.7,
|
||||
top_p=0.9,
|
||||
do_sample=True
|
||||
)
|
||||
|
||||
base_response = base_tokenizer.decode(base_outputs[0], skip_special_tokens=True)
|
||||
base_response = base_response.replace(formatted_prompt, "") # 移除提示词
|
||||
|
||||
# 保存结果
|
||||
comparison_results.append({
|
||||
"question": question,
|
||||
"finetuned_response": finetuned_response,
|
||||
"base_response": base_response,
|
||||
"reference_answer": eval_dataset[eval_dataset["Question"] == question]["Answer"].values[0] #type: ignore
|
||||
})
|
||||
|
||||
# 保存对比结果
|
||||
comparison_df = pd.DataFrame(comparison_results)
|
||||
comparison_df.to_csv("./model_comparison.csv", index=False)
|
||||
|
||||
print(f"对比评估完成，结果已保存至 model_comparison.csv")
|
||||
|
||||
# 简单统计
|
||||
print("\n===== 对比结果统计 =====")
|
||||
for i, result in enumerate(comparison_results):
|
||||
print(f"\n问题 {i+1}: {result['question']}")
|
||||
print(f"参考答案: {result['reference_answer']}")
|
||||
print(f"微调模型: {result['finetuned_response'][:100]}...")
|
||||
print(f"基础模型: {result['base_response'][:100]}...")
|
||||
print("-" * 50)
|
||||
32
config.json
Normal file
32
config.json
Normal file
@@ -0,0 +1,32 @@
|
||||
{
|
||||
"_name_or_path": "/mnt/workspace/models/Qwen/Qwen2.5-7B",
|
||||
"architectures": [
|
||||
"Qwen2ForCausalLM"
|
||||
],
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 3584,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 18944,
|
||||
"max_position_embeddings": 131072,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 28,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 4,
|
||||
"pad_token_id": 151654,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000.0,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
|
||||
"transformers_version": "4.48.3",
|
||||
"unsloth_version": "2025.3.9",
|
||||
"use_cache": true,
|
||||
"use_mrope": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 152064
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "other"}
|
||||
690
finetune_from_checkpiont.ipynb
Normal file
690
finetune_from_checkpiont.ipynb
Normal file
@@ -0,0 +1,690 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ffc392b5-82ef-4d3e-952e-d6e83317e813",
|
||||
"metadata": {
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:47:40.705036Z",
|
||||
"iopub.status.busy": "2025-03-12T06:47:40.704701Z",
|
||||
"iopub.status.idle": "2025-03-12T06:49:19.377267Z",
|
||||
"shell.execute_reply": "2025-03-12T06:49:19.376711Z",
|
||||
"shell.execute_reply.started": "2025-03-12T06:47:40.705018Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Looking in indexes: https://mirrors.cloud.aliyuncs.com/pypi/simple\n",
|
||||
"Collecting unsloth\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/97/85/657d11fef1ef2d6440ead4f0411b9b6658f53a7bf826cac1101bf78adec5/unsloth-2025.3.9-py3-none-any.whl (191 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m191.6/191.6 kB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting unsloth_zoo>=2025.3.8 (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/89/9b/20fbbe089c0e4698ddc3138b6b248ee6b8b93f5fba9b7fbd992cc77779aa/unsloth_zoo-2025.3.8-py3-none-any.whl (112 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m112.5/112.5 kB\u001b[0m \u001b[31m8.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||||
"\u001b[?25hCollecting torch>=2.4.0 (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/37/81/aa9ab58ec10264c1abe62c8b73f5086c3c558885d6beecebf699f0dbeaeb/torch-2.6.0-cp310-cp310-manylinux1_x86_64.whl (766.7 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m766.7/766.7 MB\u001b[0m \u001b[31m4.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting xformers>=0.0.27.post2 (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/55/4f/ef63f866ec7d3a23f78629604deaf379cd833fa4fd0cf7e6f8a77906f125/xformers-0.0.29.post3-cp310-cp310-manylinux_2_28_x86_64.whl (43.3 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.3/43.3 MB\u001b[0m \u001b[31m60.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: bitsandbytes in /usr/local/lib/python3.10/site-packages (from unsloth) (0.45.2)\n",
|
||||
"Collecting triton>=3.0.0 (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/01/65/3ffa90e158a2c82f0716eee8d26a725d241549b7d7aaf7e4f44ac03ebd89/triton-3.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (253.1 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m253.1/253.1 MB\u001b[0m \u001b[31m14.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: packaging in /usr/local/lib/python3.10/site-packages (from unsloth) (24.2)\n",
|
||||
"Collecting tyro (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/11/4f/5ba9e95cfe4b88ccb439b785356de7073b344abc30bf87ea767fedc0a257/tyro-0.9.16-py3-none-any.whl (117 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m117.2/117.2 kB\u001b[0m \u001b[31m25.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: transformers!=4.47.0,>=4.46.1 in /usr/local/lib/python3.10/site-packages (from unsloth) (4.48.3)\n",
|
||||
"Requirement already satisfied: datasets>=2.16.0 in /usr/local/lib/python3.10/site-packages (from unsloth) (3.2.0)\n",
|
||||
"Requirement already satisfied: sentencepiece>=0.2.0 in /usr/local/lib/python3.10/site-packages (from unsloth) (0.2.0)\n",
|
||||
"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/site-packages (from unsloth) (4.67.0)\n",
|
||||
"Requirement already satisfied: psutil in /usr/local/lib/python3.10/site-packages (from unsloth) (6.1.0)\n",
|
||||
"Requirement already satisfied: wheel>=0.42.0 in /usr/local/lib/python3.10/site-packages (from unsloth) (0.44.0)\n",
|
||||
"Requirement already satisfied: numpy in /usr/local/lib/python3.10/site-packages (from unsloth) (1.26.4)\n",
|
||||
"Requirement already satisfied: accelerate>=0.34.1 in /usr/local/lib/python3.10/site-packages (from unsloth) (1.3.0)\n",
|
||||
"Collecting trl!=0.15.0,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,<=0.15.2,>=0.7.9 (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/7b/29/25378447c48359843de0e4ce1995d367210601c3b437ddf1c779b6393d74/trl-0.15.2-py3-none-any.whl (318 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m318.9/318.9 kB\u001b[0m \u001b[31m22.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: peft!=0.11.0,>=0.7.1 in /usr/local/lib/python3.10/site-packages (from unsloth) (0.14.0)\n",
|
||||
"Requirement already satisfied: protobuf<4.0.0 in /usr/local/lib/python3.10/site-packages (from unsloth) (3.20.3)\n",
|
||||
"Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.10/site-packages (from unsloth) (0.25.2)\n",
|
||||
"Collecting hf_transfer (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/d6/d8/f87ea6f42456254b48915970ed98e993110521e9263472840174d32c880d/hf_transfer-0.1.9-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.6 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.6/3.6 MB\u001b[0m \u001b[31m71.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: diffusers in /usr/local/lib/python3.10/site-packages (from unsloth) (0.32.2)\n",
|
||||
"Requirement already satisfied: torchvision in /usr/local/lib/python3.10/site-packages (from unsloth) (0.18.1)\n",
|
||||
"Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/site-packages (from accelerate>=0.34.1->unsloth) (6.0.2)\n",
|
||||
"Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.10/site-packages (from accelerate>=0.34.1->unsloth) (0.5.2)\n",
|
||||
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (3.16.1)\n",
|
||||
"Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (19.0.0)\n",
|
||||
"Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (0.3.8)\n",
|
||||
"Requirement already satisfied: pandas in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (2.2.3)\n",
|
||||
"Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (2.32.3)\n",
|
||||
"Requirement already satisfied: xxhash in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (3.5.0)\n",
|
||||
"Requirement already satisfied: multiprocess<0.70.17 in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (0.70.16)\n",
|
||||
"Requirement already satisfied: fsspec<=2024.9.0,>=2023.1.0 in /usr/local/lib/python3.10/site-packages (from fsspec[http]<=2024.9.0,>=2023.1.0->datasets>=2.16.0->unsloth) (2024.9.0)\n",
|
||||
"Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/site-packages (from datasets>=2.16.0->unsloth) (3.11.12)\n",
|
||||
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/site-packages (from huggingface_hub->unsloth) (4.12.2)\n",
|
||||
"Requirement already satisfied: networkx in /usr/local/lib/python3.10/site-packages (from torch>=2.4.0->unsloth) (3.4.2)\n",
|
||||
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/site-packages (from torch>=2.4.0->unsloth) (3.1.4)\n",
|
||||
"Collecting nvidia-cuda-nvrtc-cu12==12.4.127 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/2c/14/91ae57cd4db3f9ef7aa99f4019cfa8d54cb4caa7e00975df6467e9725a9f/nvidia_cuda_nvrtc_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (24.6 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m81.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cuda-runtime-cu12==12.4.127 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/ea/27/1795d86fe88ef397885f2e580ac37628ed058a92ed2c39dc8eac3adf0619/nvidia_cuda_runtime_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (883 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m71.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cuda-cupti-cu12==12.4.127 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/67/42/f4f60238e8194a3106d06a058d494b18e006c10bb2b915655bd9f6ea4cb1/nvidia_cuda_cupti_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (13.8 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m102.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cudnn-cu12==9.1.0.70 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/9f/fd/713452cd72343f682b1c7b9321e23829f00b842ceaedcda96e742ea0b0b3/nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl (664.8 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m4.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cublas-cu12==12.4.5.8 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/ae/71/1c91302526c45ab494c23f61c7a84aa568b8c1f9d196efa5993957faf906/nvidia_cublas_cu12-12.4.5.8-py3-none-manylinux2014_x86_64.whl (363.4 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cufft-cu12==11.2.1.3 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/27/94/3266821f65b92b3138631e9c8e7fe1fb513804ac934485a8d05776e1dd43/nvidia_cufft_cu12-11.2.1.3-py3-none-manylinux2014_x86_64.whl (211.5 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m11.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-curand-cu12==10.3.5.147 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/8a/6d/44ad094874c6f1b9c654f8ed939590bdc408349f137f9b98a3a23ccec411/nvidia_curand_cu12-10.3.5.147-py3-none-manylinux2014_x86_64.whl (56.3 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m28.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cusolver-cu12==11.6.1.9 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/3a/e1/5b9089a4b2a4790dfdea8b3a006052cfecff58139d5a4e34cb1a51df8d6f/nvidia_cusolver_cu12-11.6.1.9-py3-none-manylinux2014_x86_64.whl (127.9 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cusparse-cu12==12.3.1.170 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/db/f7/97a9ea26ed4bbbfc2d470994b8b4f338ef663be97b8f677519ac195e113d/nvidia_cusparse_cu12-12.3.1.170-py3-none-manylinux2014_x86_64.whl (207.5 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m16.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-cusparselt-cu12==0.6.2 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/78/a8/bcbb63b53a4b1234feeafb65544ee55495e1bb37ec31b999b963cbccfd1d/nvidia_cusparselt_cu12-0.6.2-py3-none-manylinux2014_x86_64.whl (150.1 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m150.1/150.1 MB\u001b[0m \u001b[31m22.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-nccl-cu12==2.21.5 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/df/99/12cd266d6233f47d00daf3a72739872bdc10267d0383508b0b9c84a18bb6/nvidia_nccl_cu12-2.21.5-py3-none-manylinux2014_x86_64.whl (188.7 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m188.7/188.7 MB\u001b[0m \u001b[31m15.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-nvtx-cu12==12.4.127 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/87/20/199b8713428322a2f22b722c62b8cc278cc53dffa9705d744484b5035ee9/nvidia_nvtx_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (99 kB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m99.1/99.1 kB\u001b[0m \u001b[31m22.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
|
||||
"\u001b[?25hCollecting nvidia-nvjitlink-cu12==12.4.127 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/ff/ff/847841bacfbefc97a00036e0fce5a0f086b640756dc38caea5e1bb002655/nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m113.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting sympy==1.13.1 (from torch>=2.4.0->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/b2/fe/81695a1aa331a842b582453b605175f419fe8540355886031328089d840a/sympy-1.13.1-py3-none-any.whl (6.2 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.2/6.2 MB\u001b[0m \u001b[31m116.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m\n",
|
||||
"\u001b[?25hRequirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/site-packages (from sympy==1.13.1->torch>=2.4.0->unsloth) (1.3.0)\n",
|
||||
"Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/site-packages (from transformers!=4.47.0,>=4.46.1->unsloth) (2024.11.6)\n",
|
||||
"Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.10/site-packages (from transformers!=4.47.0,>=4.46.1->unsloth) (0.21.0)\n",
|
||||
"Requirement already satisfied: rich in /usr/local/lib/python3.10/site-packages (from trl!=0.15.0,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,<=0.15.2,>=0.7.9->unsloth) (13.9.4)\n",
|
||||
"Collecting cut_cross_entropy (from unsloth_zoo>=2025.3.8->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/df/5f/62fdb048f84d19e2123b6bbd722fe09c8c79b4964c50094d1e979db808e2/cut_cross_entropy-25.1.1-py3-none-any.whl (22 kB)\n",
|
||||
"Requirement already satisfied: pillow in /usr/local/lib/python3.10/site-packages (from unsloth_zoo>=2025.3.8->unsloth) (11.0.0)\n",
|
||||
"Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.10/site-packages (from diffusers->unsloth) (8.5.0)\n",
|
||||
"INFO: pip is looking at multiple versions of torchvision to determine which version is compatible with other requirements. This could take a while.\n",
|
||||
"Collecting torchvision (from unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/5e/44/32e2d2d174391374d5ff3c4691b802e8efda9ae27ab9062eca2255b006af/torchvision-0.21.0-cp310-cp310-manylinux1_x86_64.whl (7.2 MB)\n",
|
||||
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m118.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0ma \u001b[36m0:00:01\u001b[0m\n",
|
||||
"\u001b[?25hCollecting docstring-parser>=0.15 (from tyro->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/d5/7c/e9fcff7623954d86bdc17782036cbf715ecab1bec4847c008557affe1ca8/docstring_parser-0.16-py3-none-any.whl (36 kB)\n",
|
||||
"Collecting shtab>=1.5.6 (from tyro->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/e2/d1/a1d3189e7873408b9dc396aef0d7926c198b0df2aa3ddb5b539d3e89a70f/shtab-1.7.1-py3-none-any.whl (14 kB)\n",
|
||||
"Collecting typeguard>=4.0.0 (from tyro->unsloth)\n",
|
||||
" Downloading https://mirrors.cloud.aliyuncs.com/pypi/packages/cf/4b/9a77dc721aa0b7f74440a42e4ef6f9a4fae7324e17f64f88b96f4c25cc05/typeguard-4.4.2-py3-none-any.whl (35 kB)\n",
|
||||
"Requirement already satisfied: aiohappyeyeballs>=2.3.0 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (2.4.6)\n",
|
||||
"Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.3.2)\n",
|
||||
"Requirement already satisfied: async-timeout<6.0,>=4.0 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (5.0.1)\n",
|
||||
"Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (24.2.0)\n",
|
||||
"Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.5.0)\n",
|
||||
"Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (6.1.0)\n",
|
||||
"Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (0.2.1)\n",
|
||||
"Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.10/site-packages (from aiohttp->datasets>=2.16.0->unsloth) (1.18.3)\n",
|
||||
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/site-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (3.4.0)\n",
|
||||
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/site-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (3.10)\n",
|
||||
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/site-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (2.2.3)\n",
|
||||
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/site-packages (from requests>=2.32.2->datasets>=2.16.0->unsloth) (2024.8.30)\n",
|
||||
"Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/site-packages (from rich->trl!=0.15.0,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,<=0.15.2,>=0.7.9->unsloth) (3.0.0)\n",
|
||||
"Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/site-packages (from rich->trl!=0.15.0,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,<=0.15.2,>=0.7.9->unsloth) (2.18.0)\n",
|
||||
"Requirement already satisfied: zipp>=3.20 in /usr/local/lib/python3.10/site-packages (from importlib-metadata->diffusers->unsloth) (3.20.2)\n",
|
||||
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/site-packages (from jinja2->torch>=2.4.0->unsloth) (2.1.5)\n",
|
||||
"Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/site-packages (from pandas->datasets>=2.16.0->unsloth) (2.9.0.post0)\n",
|
||||
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/site-packages (from pandas->datasets>=2.16.0->unsloth) (2025.1)\n",
|
||||
"Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/site-packages (from pandas->datasets>=2.16.0->unsloth) (2025.1)\n",
|
||||
"Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/site-packages (from markdown-it-py>=2.2.0->rich->trl!=0.15.0,!=0.9.0,!=0.9.1,!=0.9.2,!=0.9.3,<=0.15.2,>=0.7.9->unsloth) (0.1.2)\n",
|
||||
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas->datasets>=2.16.0->unsloth) (1.16.0)\n",
|
||||
"\u001b[33mDEPRECATION: omegaconf 2.0.6 has a non-standard dependency specifier PyYAML>=5.1.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of omegaconf or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
|
||||
"\u001b[0m\u001b[33mDEPRECATION: pytorch-lightning 1.7.7 has a non-standard dependency specifier torch>=1.9.*. pip 24.0 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of pytorch-lightning or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n",
|
||||
"\u001b[0mInstalling collected packages: triton, nvidia-cusparselt-cu12, typeguard, sympy, shtab, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, hf_transfer, docstring-parser, nvidia-cusparse-cu12, nvidia-cudnn-cu12, tyro, nvidia-cusolver-cu12, torch, xformers, torchvision, cut_cross_entropy, trl, unsloth_zoo, unsloth\n",
|
||||
" Attempting uninstall: triton\n",
|
||||
" Found existing installation: triton 2.3.1\n",
|
||||
" Uninstalling triton-2.3.1:\n",
|
||||
" Successfully uninstalled triton-2.3.1\n",
|
||||
" Attempting uninstall: typeguard\n",
|
||||
" Found existing installation: typeguard 2.13.3\n",
|
||||
" Uninstalling typeguard-2.13.3:\n",
|
||||
" Successfully uninstalled typeguard-2.13.3\n",
|
||||
" Attempting uninstall: sympy\n",
|
||||
" Found existing installation: sympy 1.13.3\n",
|
||||
" Uninstalling sympy-1.13.3:\n",
|
||||
" Successfully uninstalled sympy-1.13.3\n",
|
||||
" Attempting uninstall: nvidia-nvtx-cu12\n",
|
||||
" Found existing installation: nvidia-nvtx-cu12 12.1.105\n",
|
||||
" Uninstalling nvidia-nvtx-cu12-12.1.105:\n",
|
||||
" Successfully uninstalled nvidia-nvtx-cu12-12.1.105\n",
|
||||
" Attempting uninstall: nvidia-nvjitlink-cu12\n",
|
||||
" Found existing installation: nvidia-nvjitlink-cu12 12.6.77\n",
|
||||
" Uninstalling nvidia-nvjitlink-cu12-12.6.77:\n",
|
||||
" Successfully uninstalled nvidia-nvjitlink-cu12-12.6.77\n",
|
||||
" Attempting uninstall: nvidia-nccl-cu12\n",
|
||||
" Found existing installation: nvidia-nccl-cu12 2.20.5\n",
|
||||
" Uninstalling nvidia-nccl-cu12-2.20.5:\n",
|
||||
" Successfully uninstalled nvidia-nccl-cu12-2.20.5\n",
|
||||
" Attempting uninstall: nvidia-curand-cu12\n",
|
||||
" Found existing installation: nvidia-curand-cu12 10.3.2.106\n",
|
||||
" Uninstalling nvidia-curand-cu12-10.3.2.106:\n",
|
||||
" Successfully uninstalled nvidia-curand-cu12-10.3.2.106\n",
|
||||
" Attempting uninstall: nvidia-cufft-cu12\n",
|
||||
" Found existing installation: nvidia-cufft-cu12 11.0.2.54\n",
|
||||
" Uninstalling nvidia-cufft-cu12-11.0.2.54:\n",
|
||||
" Successfully uninstalled nvidia-cufft-cu12-11.0.2.54\n",
|
||||
" Attempting uninstall: nvidia-cuda-runtime-cu12\n",
|
||||
" Found existing installation: nvidia-cuda-runtime-cu12 12.1.105\n",
|
||||
" Uninstalling nvidia-cuda-runtime-cu12-12.1.105:\n",
|
||||
" Successfully uninstalled nvidia-cuda-runtime-cu12-12.1.105\n",
|
||||
" Attempting uninstall: nvidia-cuda-nvrtc-cu12\n",
|
||||
" Found existing installation: nvidia-cuda-nvrtc-cu12 12.1.105\n",
|
||||
" Uninstalling nvidia-cuda-nvrtc-cu12-12.1.105:\n",
|
||||
" Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.1.105\n",
|
||||
" Attempting uninstall: nvidia-cuda-cupti-cu12\n",
|
||||
" Found existing installation: nvidia-cuda-cupti-cu12 12.1.105\n",
|
||||
" Uninstalling nvidia-cuda-cupti-cu12-12.1.105:\n",
|
||||
" Successfully uninstalled nvidia-cuda-cupti-cu12-12.1.105\n",
|
||||
" Attempting uninstall: nvidia-cublas-cu12\n",
|
||||
" Found existing installation: nvidia-cublas-cu12 12.1.3.1\n",
|
||||
" Uninstalling nvidia-cublas-cu12-12.1.3.1:\n",
|
||||
" Successfully uninstalled nvidia-cublas-cu12-12.1.3.1\n",
|
||||
" Attempting uninstall: nvidia-cusparse-cu12\n",
|
||||
" Found existing installation: nvidia-cusparse-cu12 12.1.0.106\n",
|
||||
" Uninstalling nvidia-cusparse-cu12-12.1.0.106:\n",
|
||||
" Successfully uninstalled nvidia-cusparse-cu12-12.1.0.106\n",
|
||||
" Attempting uninstall: nvidia-cudnn-cu12\n",
|
||||
" Found existing installation: nvidia-cudnn-cu12 8.9.2.26\n",
|
||||
" Uninstalling nvidia-cudnn-cu12-8.9.2.26:\n",
|
||||
" Successfully uninstalled nvidia-cudnn-cu12-8.9.2.26\n",
|
||||
" Attempting uninstall: nvidia-cusolver-cu12\n",
|
||||
" Found existing installation: nvidia-cusolver-cu12 11.4.5.107\n",
|
||||
" Uninstalling nvidia-cusolver-cu12-11.4.5.107:\n",
|
||||
" Successfully uninstalled nvidia-cusolver-cu12-11.4.5.107\n",
|
||||
" Attempting uninstall: torch\n",
|
||||
" Found existing installation: torch 2.3.1\n",
|
||||
" Uninstalling torch-2.3.1:\n",
|
||||
" Successfully uninstalled torch-2.3.1\n",
|
||||
" Attempting uninstall: xformers\n",
|
||||
" Found existing installation: xformers 0.0.27\n",
|
||||
" Uninstalling xformers-0.0.27:\n",
|
||||
" Successfully uninstalled xformers-0.0.27\n",
|
||||
" Attempting uninstall: torchvision\n",
|
||||
" Found existing installation: torchvision 0.18.1\n",
|
||||
" Uninstalling torchvision-0.18.1:\n",
|
||||
" Successfully uninstalled torchvision-0.18.1\n",
|
||||
" Attempting uninstall: trl\n",
|
||||
" Found existing installation: trl 0.15.0\n",
|
||||
" Uninstalling trl-0.15.0:\n",
|
||||
" Successfully uninstalled trl-0.15.0\n",
|
||||
"\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
|
||||
"xtuner 0.1.23 requires lagent>=0.1.2, which is not installed.\n",
|
||||
"xtuner 0.1.23 requires mmengine>=0.10.3, which is not installed.\n",
|
||||
"autoawq 0.2.8 requires huggingface-hub>=0.26.5, but you have huggingface-hub 0.25.2 which is incompatible.\n",
|
||||
"autoawq 0.2.8 requires transformers<=4.47.1,>=4.45.0, but you have transformers 4.48.3 which is incompatible.\n",
|
||||
"fairseq 0.12.2 requires hydra-core<1.1,>=1.0.7, but you have hydra-core 1.3.2 which is incompatible.\n",
|
||||
"fastai 2.7.18 requires torch<2.6,>=1.10, but you have torch 2.6.0 which is incompatible.\n",
|
||||
"funcodec 0.2.0 requires typeguard==2.13.3, but you have typeguard 4.4.2 which is incompatible.\n",
|
||||
"lmdeploy 0.6.2 requires peft<=0.11.1, but you have peft 0.14.0 which is incompatible.\n",
|
||||
"lmdeploy 0.6.2 requires torch<=2.4.0,>=2.0.0, but you have torch 2.6.0 which is incompatible.\n",
|
||||
"lmdeploy 0.6.2 requires torchvision<=0.19.0,>=0.15.0, but you have torchvision 0.21.0 which is incompatible.\n",
|
||||
"lmdeploy 0.6.2 requires triton<=3.0.0,>=2.2.0; sys_platform == \"linux\", but you have triton 3.2.0 which is incompatible.\n",
|
||||
"pai-easycv 0.11.6 requires timm==0.5.4, but you have timm 1.0.14 which is incompatible.\n",
|
||||
"torchaudio 2.3.1 requires torch==2.3.1, but you have torch 2.6.0 which is incompatible.\n",
|
||||
"vllm 0.5.3 requires torch==2.3.1, but you have torch 2.6.0 which is incompatible.\n",
|
||||
"vllm 0.5.3 requires torchvision==0.18.1, but you have torchvision 0.21.0 which is incompatible.\n",
|
||||
"vllm 0.5.3 requires xformers==0.0.27, but you have xformers 0.0.29.post3 which is incompatible.\n",
|
||||
"vllm-flash-attn 2.5.9.post1 requires torch==2.3.1, but you have torch 2.6.0 which is incompatible.\u001b[0m\u001b[31m\n",
|
||||
"\u001b[0mSuccessfully installed cut_cross_entropy-25.1.1 docstring-parser-0.16 hf_transfer-0.1.9 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-cusparselt-cu12-0.6.2 nvidia-nccl-cu12-2.21.5 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.4.127 shtab-1.7.1 sympy-1.13.1 torch-2.6.0 torchvision-0.21.0 triton-3.2.0 trl-0.15.2 typeguard-4.4.2 tyro-0.9.16 unsloth-2025.3.9 unsloth_zoo-2025.3.8 xformers-0.0.29.post3\n",
|
||||
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
|
||||
"\u001b[0m\n",
|
||||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.0.1\u001b[0m\n",
|
||||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!pip install unsloth"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1c5475de-22a3-43ef-a15a-62b26d3e69a8",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!python -c \"from modelscope.hub.snapshot_download import snapshot_download; snapshot_download('Qwen/Qwen2.5-7B', cache_dir='/mnt/workspace/models')\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "a69c658c-6d31-4536-aa1f-7fbd118a983f",
|
||||
"metadata": {
|
||||
"ExecutionIndicator": {
|
||||
"show": true
|
||||
},
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:49:19.378570Z",
|
||||
"iopub.status.busy": "2025-03-12T06:49:19.378272Z",
|
||||
"iopub.status.idle": "2025-03-12T06:51:15.648856Z",
|
||||
"shell.execute_reply": "2025-03-12T06:51:15.648229Z",
|
||||
"shell.execute_reply.started": "2025-03-12T06:49:19.378550Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"🦥 Unsloth: Will patch your computer to enable 2x faster free finetuning.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"2025-03-12 14:49:24.753713: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
|
||||
"2025-03-12 14:49:24.793058: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
|
||||
"To enable the following instructions: AVX2 AVX512F AVX512_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
|
||||
"2025-03-12 14:49:25.791081: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"🦥 Unsloth Zoo will now patch everything to make training faster!\n",
|
||||
"[2025-03-12 14:49:31,238] [INFO] [real_accelerator.py:222:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stderr",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"df: /root/.triton/autotune: 没有那个文件或目录\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"WARNING 03-12 14:49:32 _custom_ops.py:14] Failed to import from vllm._C with ImportError('/usr/local/lib/python3.10/site-packages/vllm/_C.abi3.so: undefined symbol: _ZN5torch3jit11parseSchemaERKSs')\n",
|
||||
"==((====))== Unsloth 2025.3.9: Fast Qwen2 patching. Transformers: 4.48.3. vLLM: 0.5.3.\n",
|
||||
" \\\\ /| NVIDIA A10. Num GPUs = 1. Max memory: 23.69 GB. Platform: Linux.\n",
|
||||
"O^O/ \\_/ \\ Torch: 2.6.0+cu124. CUDA: 8.6. CUDA Toolkit: 12.4. Triton: 3.2.0\n",
|
||||
"\\ / Bfloat16 = TRUE. FA [Xformers = 0.0.29.post3. FA2 = True]\n",
|
||||
" \"-____-\" Free license: http://github.com/unslothai/unsloth\n",
|
||||
"Unsloth: Fast downloading is enabled - ignore downloading bars which are red colored!\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "abb304d817e14275824b51922d51af3b",
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
},
|
||||
"text/plain": [
|
||||
"Loading checkpoint shards: 0%| | 0/4 [00:00<?, ?it/s]"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
},
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"/mnt/workspace/models/Qwen/Qwen2.5-7B does not have a padding token! Will use pad_token = <|vision_pad|>.\n",
|
||||
"成功从检查点加载模型\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from unsloth import FastLanguageModel\n",
|
||||
"import torch\n",
|
||||
"import os\n",
|
||||
"\n",
|
||||
"max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally!\n",
|
||||
"dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n",
|
||||
"load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.\n",
|
||||
"\n",
|
||||
"# 基础模型路径\n",
|
||||
"base_model_path = \"/mnt/workspace/models/Qwen/Qwen2.5-7B\"\n",
|
||||
"# 检查点路径 - 这是之前训练保存的检查点\n",
|
||||
"\n",
|
||||
"# 从基础模型和检查点加载模型\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"model, tokenizer = FastLanguageModel.from_pretrained(\n",
|
||||
" model_name = base_model_path,\n",
|
||||
" max_seq_length = max_seq_length,\n",
|
||||
" dtype = dtype,\n",
|
||||
" load_in_4bit = load_in_4bit,\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"print(\"成功从检查点加载模型\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "075045ac-b3f9-410c-8def-ee00d009e2a3",
|
||||
"metadata": {
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:51:15.649791Z",
|
||||
"iopub.status.busy": "2025-03-12T06:51:15.649601Z",
|
||||
"iopub.status.idle": "2025-03-12T06:51:15.654695Z",
|
||||
"shell.execute_reply": "2025-03-12T06:51:15.654141Z",
|
||||
"shell.execute_reply.started": "2025-03-12T06:51:15.649774Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# -*- coding: utf-8 -*-\n",
|
||||
"import json\n",
|
||||
"from datasets import Dataset\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"custom_prompt = \"\"\"下面列出了一个问题. 请写出问题的答案.\n",
|
||||
"### 问题:\n",
|
||||
"{}\n",
|
||||
"### 答案:\n",
|
||||
"{}\"\"\"\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"class LocalJsonDataset:\n",
|
||||
" def __init__(self, json_file, tokenizer, max_seq_length=2048):\n",
|
||||
" self.json_file = json_file\n",
|
||||
" self.tokenizer = tokenizer\n",
|
||||
" self.max_seq_length = max_seq_length\n",
|
||||
" self.dataset = self.load_dataset()\n",
|
||||
"\n",
|
||||
" def load_dataset(self):\n",
|
||||
" with open(self.json_file, 'r', encoding='utf-8') as f:\n",
|
||||
" data = json.load(f)\n",
|
||||
"\n",
|
||||
" texts = []\n",
|
||||
" for item in data:\n",
|
||||
" text = custom_prompt.format(item['Question'], item['Response']) + self.tokenizer.eos_token\n",
|
||||
" texts.append(text)\n",
|
||||
"\n",
|
||||
" dataset_dict = {\n",
|
||||
" 'text': texts # 添加'text'字段以适配SFTTrainer\n",
|
||||
" }\n",
|
||||
"\n",
|
||||
" dataset = Dataset.from_dict(dataset_dict)\n",
|
||||
" return dataset\n",
|
||||
"\n",
|
||||
" def get_dataset(self):\n",
|
||||
" return self.dataset"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "2bfabb01-41e5-45ab-b2bc-aec847e0d8a5",
|
||||
"metadata": {
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:51:15.656107Z",
|
||||
"iopub.status.busy": "2025-03-12T06:51:15.655827Z",
|
||||
"iopub.status.idle": "2025-03-12T06:51:16.374665Z",
|
||||
"shell.execute_reply": "2025-03-12T06:51:16.374194Z",
|
||||
"shell.execute_reply.started": "2025-03-12T06:51:15.656092Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# -*- coding: utf-8 -*-\n",
|
||||
"# 加载和预处理数据集\n",
|
||||
"custom_dataset = LocalJsonDataset(json_file='/mnt/workspace/medical_o1_sft_Chinese.json', tokenizer=tokenizer, max_seq_length=max_seq_length)\n",
|
||||
"dataset = custom_dataset.get_dataset()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "ad5db9ae-664a-401c-bd0a-cf00e22112a0",
|
||||
"metadata": {
|
||||
"ExecutionIndicator": {
|
||||
"show": true
|
||||
},
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:51:16.375417Z",
|
||||
"iopub.status.busy": "2025-03-12T06:51:16.375256Z",
|
||||
"iopub.status.idle": "2025-03-12T06:51:21.278991Z",
|
||||
"shell.execute_reply": "2025-03-12T06:51:21.278537Z",
|
||||
"shell.execute_reply.started": "2025-03-12T06:51:16.375401Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model = FastLanguageModel.get_peft_model(\n",
|
||||
" model,\n",
|
||||
" r = 16, # Choose any number > 0 ! Suggested 8, 16, 32, 64, 128\n",
|
||||
" target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
|
||||
" \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
|
||||
" lora_alpha = 16,\n",
|
||||
" lora_dropout = 0, # Supports any, but = 0 is optimized\n",
|
||||
" bias = \"none\", # Supports any, but = \"none\" is optimized\n",
|
||||
" # [NEW] \"unsloth\" uses 30% less VRAM, fits 2x larger batch sizes!\n",
|
||||
" use_gradient_checkpointing = \"unsloth\", # True or \"unsloth\" for very long context\n",
|
||||
" random_state = 3407,\n",
|
||||
" use_rslora = False, # We support rank stabilized LoRA\n",
|
||||
" loftq_config = None, # And LoftQ\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "2c3dd4cf-28ba-46ff-a4cb-1f239f4d9920",
|
||||
"metadata": {
|
||||
"ExecutionIndicator": {
|
||||
"show": true
|
||||
},
|
||||
"execution": {
|
||||
"iopub.execute_input": "2025-03-12T06:51:21.279806Z",
|
||||
"iopub.status.busy": "2025-03-12T06:51:21.279624Z"
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"application/vnd.jupyter.widget-view+json": {
|
||||
"model_id": "686840cdebdf44159b4cf2fa47c0f0ff",
|
||||
"version_major": 2,
|
||||
"version_minor": 0
|
||||
},
|
||||
"text/plain": [
|
||||
"Tokenizing to [\"text\"] (num_proc=2): 0%| | 0/24772 [00:00<?, ? examples/s]"
|
||||
]
|
||||
},
|
||||
"metadata": {},
|
||||
"output_type": "display_data"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from trl import SFTTrainer\n",
|
||||
"from transformers import TrainingArguments\n",
|
||||
"from unsloth import is_bfloat16_supported\n",
|
||||
"\n",
|
||||
"trainer = SFTTrainer(\n",
|
||||
" model = model,\n",
|
||||
" tokenizer = tokenizer,\n",
|
||||
" train_dataset = dataset,\n",
|
||||
" dataset_text_field = \"text\",\n",
|
||||
" max_seq_length = max_seq_length,\n",
|
||||
" dataset_num_proc = 2,\n",
|
||||
" packing = False, # Can make training 5x faster for short sequences.\n",
|
||||
" args = TrainingArguments(\n",
|
||||
" per_device_train_batch_size = 2,\n",
|
||||
" gradient_accumulation_steps = 4,\n",
|
||||
" warmup_steps = 5,\n",
|
||||
" num_train_epochs = 3, # Set this for 1 full training run.\n",
|
||||
" # max_steps = 128,\n",
|
||||
" learning_rate = 5e-5,\n",
|
||||
" fp16 = not is_bfloat16_supported(),\n",
|
||||
" bf16 = is_bfloat16_supported(),\n",
|
||||
" logging_steps = 1,\n",
|
||||
" optim = \"adamw_8bit\",\n",
|
||||
" weight_decay = 0.01,\n",
|
||||
" lr_scheduler_type = \"linear\",\n",
|
||||
" seed = 3407,\n",
|
||||
" output_dir = \"outputs\",\n",
|
||||
" report_to = \"none\", # Use this for WandB etc\n",
|
||||
" ),\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "698c1056-aa04-42c0-9691-f01c08e4f536",
|
||||
"metadata": {
|
||||
"ExecutionIndicator": {
|
||||
"show": true
|
||||
},
|
||||
"scrolled": true,
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# 开始训练\n",
|
||||
"trainer.train()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "90e8dca0",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# 或者选择从checkpoint继续训练\n",
|
||||
"trainer.train(resume_from_checkpoint = True)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "24af8b57-2e0f-485e-8712-18787fd8da14",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"model"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "5e878fa3-03c9-47f9-8d46-a20702980851",
|
||||
"metadata": {
|
||||
"ExecutionIndicator": {
|
||||
"show": true
|
||||
},
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"FastLanguageModel.for_inference(model) # Enable native 2x faster inference\n",
|
||||
"inputs = tokenizer(\n",
|
||||
"[\n",
|
||||
" custom_prompt.format(\n",
|
||||
" \"经常性反酸打嗝，体重下降，腹部CT完全正常、肝肾功能正常，癌胚抗原指标正常，这种情况下最可能的诊断是什么\", # input\n",
|
||||
" \"\", # output - leave this blank for generation!\n",
|
||||
" )\n",
|
||||
"], return_tensors = \"pt\").to(\"cuda\")\n",
|
||||
"\n",
|
||||
"from transformers import TextStreamer\n",
|
||||
"text_streamer = TextStreamer(tokenizer)\n",
|
||||
"_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 2048)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f3a6b4dd-6922-45f5-9548-f5ca41f0e735",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"new_model_local = \"qwen-medical-7b\"\n",
|
||||
"model.save_pretrained_merged(new_model_local, tokenizer, save_method = \"merged_16bit\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "90de7813",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"保存至modelscope"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "307724e8",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"！modelscope login --token *******\n",
|
||||
"\n",
|
||||
"！modelscope upload username/qwen-medical /mnt/workspace/qwen-medical-7b"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "1ffde40c",
|
||||
"metadata": {},
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.14"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
8
generation_config.json
Normal file
8
generation_config.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151643,
|
||||
"max_length": 131072,
|
||||
"max_new_tokens": 2048,
|
||||
"pad_token_id": 151654,
|
||||
"transformers_version": "4.48.3"
|
||||
}
|
||||
151388
merges.txt
Normal file
151388
merges.txt
Normal file
File diff suppressed because it is too large
Load Diff
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 sha256:7146f39fa17e035f19bc1580dd9fb59e0e8cb553347b5c3e1dbc62fcef0d7697
|
||||
size 4877660776
|
||||
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 sha256:6c9a06dbd7ebbb29de9431d4fd5b95c02aac547eac6e7c505376b55a53c1ac4c
|
||||
size 4932751008
|
||||
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 sha256:54bd7f34d01e0fcc84409113d3400c737881fcbbe0f25ab4e982d50ff0f9842c
|
||||
size 4330865200
|
||||
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 sha256:5be8567a86b9f8fdf251358a5757baf1e45239e4ba2ed2bb04d81d824a7031c5
|
||||
size 1089994880
|
||||
346
model.safetensors.index.json
Normal file
346
model.safetensors.index.json
Normal file
@@ -0,0 +1,346 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_size": 15231233024
|
||||
},
|
||||
"weight_map": {
|
||||
"lm_head.weight": "model-00004-of-00004.safetensors",
|
||||
"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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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-00003-of-00004.safetensors",
|
||||
"model.layers.18.mlp.down_proj.weight": "model-00003-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-00003-of-00004.safetensors",
|
||||
"model.layers.18.self_attn.k_proj.bias": "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.bias": "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.bias": "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-00003-of-00004.safetensors",
|
||||
"model.layers.19.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.19.self_attn.v_proj.weight": "model-00003-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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.q_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.v_proj.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.20.self_attn.v_proj.weight": "model-00003-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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "model-00003-of-00004.safetensors",
|
||||
"model.layers.27.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.self_attn.k_proj.bias": "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.bias": "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.bias": "model-00001-of-00004.safetensors",
|
||||
"model.layers.3.self_attn.v_proj.weight": "model-00001-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.self_attn.k_proj.bias": "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.bias": "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.bias": "model-00001-of-00004.safetensors",
|
||||
"model.layers.4.self_attn.v_proj.weight": "model-00001-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.self_attn.k_proj.bias": "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.bias": "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.bias": "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.self_attn.k_proj.bias": "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.bias": "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.bias": "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-00001-of-00004.safetensors",
|
||||
"model.layers.7.mlp.down_proj.weight": "model-00001-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-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.k_proj.bias": "model-00001-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.bias": "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.bias": "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.self_attn.k_proj.bias": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-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.self_attn.k_proj.bias": "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.bias": "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.bias": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00003-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
25
special_tokens_map.json
Normal file
25
special_tokens_map.json
Normal file
@@ -0,0 +1,25 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": "<|vision_pad|>"
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
|
||||
size 11421896
|
||||
209
tokenizer_config.json
Normal file
209
tokenizer_config.json
Normal file
@@ -0,0 +1,209 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151657": {
|
||||
"content": "<tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151658": {
|
||||
"content": "</tool_call>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151659": {
|
||||
"content": "<|fim_prefix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151660": {
|
||||
"content": "<|fim_middle|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151661": {
|
||||
"content": "<|fim_suffix|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151662": {
|
||||
"content": "<|fim_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151663": {
|
||||
"content": "<|repo_name|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
},
|
||||
"151664": {
|
||||
"content": "<|file_sep|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": false
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
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