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https://github.com/ssbuild/qwen_finetuning

qwen-7b and qwen-14b finetuning
https://github.com/ssbuild/qwen_finetuning

adalora ia3 lora qlora qwen qwen-14b qwen-7b sfml

Last synced: 4 days ago
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qwen-7b and qwen-14b finetuning

Host: GitHub
URL: https://github.com/ssbuild/qwen_finetuning
Owner: ssbuild
License: apache-2.0
Created: 2023-08-03T07:27:23.000Z (over 1 year ago)
Default Branch: dev
Last Pushed: 2024-04-21T17:07:24.000Z (7 months ago)
Last Synced: 2024-04-28T04:59:07.706Z (7 months ago)
Topics: adalora, ia3, lora, qlora, qwen, qwen-14b, qwen-7b, sfml
Language: Python
Homepage:
Size: 505 KB
Stars: 69
Watchers: 2
Forks: 5
Open Issues: 2
Metadata Files:
- Readme: README.MD
- License: LICENSE

Awesome Lists containing this project

README

## statement
- [deep_training](https://github.com/ssbuild/deep_training)

```text
2024-04-22 简化
2023-12-02 update qwen model 1.8b 7b 12b 72b
2023-10-09 support accelerator trainer
2023-10-07 support colossalai trainer
2023-09-26 support transformers trainer
2023-09-25 0.2.4 support qwen-7b 新版和 qwen-14b ，旧版不再支持，旧版可以安装 deep_training <= 0.2.3
support transformers trainer
2023-08-11 aigc-zoo 0.1.17.post0 update config , 更新下官方权重配置文件
dev 分支加一些新功能和想法如果求稳定，请使用 stable分支

```

## install
- pip install -U -r requirements.txt
- 如果无法安装 , 可以切换官方源 pip install -i https://pypi.org/simple -U -r requirements.txt

```text

# flash-attention对显卡算例要求算力7.5 以上，下面可选安装，如果卡不支持可以不安装。
git clone -b https://github.com/Dao-AILab/flash-attention
cd flash-attention && pip install .
pip install csrc/layer_norm
pip install csrc/rotary
```

## weight
- [Qwen-1_8B](https://huggingface.co/Qwen/Qwen-1_8B)
- [Qwen-1_8B-Chat](https://huggingface.co/Qwen/Qwen-1_8B-Chat)
- [Qwen-7B](https://huggingface.co/Qwen/Qwen-7B)
- [Qwen-7B-Chat](https://huggingface.co/Qwen/Qwen-7B-Chat)
- [Qwen-14B](https://huggingface.co/Qwen/Qwen-14B)
- [Qwen-14B-Chat](https://huggingface.co/Qwen/Qwen-14B-Chat)
- [Qwen-72B](https://huggingface.co/Qwen/Qwen-72B)
- [Qwen-72B-Chat](https://huggingface.co/Qwen/Qwen-72B-Chat)

## data sample
- [open_data 不定时开放新数据集](https://github.com/ssbuild/open_data)
- [react_prompt](assets/react_prompt.md)

```text
数据示例
例子依次分别是工具，对话，对话，对话
数据构建sample 参考 data/make_data_example.py
数组组成
role: 可选字段(str) 标志 q字段角色, one of user system, observation ，system 标识是否为 system prompt , system prompt a 空
q: 问题
a: 回答

注意事项:
a字段：对于普通对话，a即为回答。
细节可以参考 assets/react_prompt.md
```

```json
{"id": 1, "paragraph": [{"role": "system", "q": "You are a helpful assistant.", "a": ""}, {"role": "user", "q": "Answer the following questions as best you can. You have access to the following tools:\n\nquark_search: Call this tool to interact with the 夸克搜索 API. What is the 夸克搜索 API useful for? 夸克搜索是一个通用搜索引擎，可用于访问互联网、查询百科知识、了解时事新闻等。 Parameters: [{\"name\": \"search_query\", \"description\": \"搜索关键词或短语\", \"required\": true, \"schema\": {\"type\": \"string\"}}] Format the arguments as a JSON object.\n\nimage_gen: Call this tool to interact with the 通义万相 API. What is the 通义万相 API useful for? 通义万相是一个AI绘画（图像生成）服务，输入文本描述，返回根据文本作画得到的图片的URL Parameters: [{\"name\": \"query\", \"description\": \"中文关键词，描述了希望图像具有什么内容\", \"required\": true, \"schema\": {\"type\": \"string\"}}] Format the arguments as a JSON object.\n\nUse the following format:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [quark_search,image_gen]\nAction Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Observation can be repeated zero or more times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n\nBegin!\n\nQuestion: 现在给我画个五彩斑斓的黑", "a": "\nThought: 我应该使用通义万相API来生成一张五彩斑斓的黑的图片。\nAction: image_gen\nAction Input: {\"query\": \"五彩斑斓的黑\"}\n "}, {"role": "observation", "q": "Observation: \n{\"status_code\": 200, \"request_id\": \"3d894da2-0e26-9b7c-bd90-102e5250ae03\", \"code\": null, \"message\": \"\", \"output\": {\"task_id\": \"2befaa09-a8b3-4740-ada9-4d00c2758b05\", \"task_status\": \"SUCCEEDED\", \"results\": [{\"url\": \"https://dashscope-result-sh.oss-cn-shanghai.aliyuncs.com/1e5e2015/20230801/1509/6b26bb83-469e-4c70-bff4-a9edd1e584f3-1.png\"}], \"task_metrics\": {\"TOTAL\": 1, \"SUCCEEDED\": 1, \"FAILED\": 0}}, \"usage\": {\"image_count\": 1}}\n", "a": "\nThought: 我已经成功使用通义万相API生成了一张五彩斑斓的黑的图片。\nFinal Answer: 我已经成功使用通义万相API生成了一张五彩斑斓的黑的图片https://dashscope-result-sh.oss-cn-shanghai.aliyuncs.com/1e5e2015/20230801/1509/6b26bb83-469e-4c70-bff4-a9edd1e584f3-1.png。\n "}]}
{"id": 2, "paragraph": [{"role": "system", "q": "You are a helpful assistant.", "a": ""}, {"q": "从南京到上海的路线", "a": "你好，南京到上海的路线如下：\n1. 南京到上海，可以乘坐南京地铁1号线，在南京站乘坐轨道交通1号线。\n2. 南京到浦东机场，可以搭乘上海地铁1号，在陆家嘴站乘坐地铁1线，在浦东国际机场站乘坐机场快线，前往上海浦东国际机场。\n3. 上海到南京，可以换乘上海地铁2号线，从南京站换乘地铁2线，再从南京南站换乘地铁1路，然后到达上海站"}]}
{"id": 3, "paragraph": [{"role": "system", "q": "You are a helpful assistant.", "a": ""}, {"q": "写一个诗歌，关于冬天", "a": "冬夜寂静冷，\n云在天边飘，\n冰封白雪上， \n寒冷像一场雪。\n \n雪花融化成冰，\n像那雪花飘洒，\n在寒冷的冬天，\n感受春天的喜悦。\n 冬日里，\n风雪渐消，\n一片寂静，\n把快乐和温暖带回家。"}]}
{"id": 4, "paragraph": [{"role": "system", "q": "You are a helpful assistant.", "a": ""}, {"q": "晚上睡不着应该怎么办", "a": "晚上睡不着可能会让你感到焦虑或不舒服,但以下是一些可以帮助你入睡的方法:\n\n1. 制定规律的睡眠时间表:保持规律的睡眠时间表可以帮助你建立健康的睡眠习惯,使你更容易入睡。尽量在每天的相同时间上床,并在同一时间起床。\n2. 创造一个舒适的睡眠环境:确保睡眠环境舒适,安静,黑暗且温度适宜。可以使用舒适的床上用品,并保持房间通风。\n3. 放松身心:在睡前做些放松的活动,例如泡个热水澡,听些轻柔的音乐,阅读一些有趣的书籍等,有助于缓解紧张和焦虑,使你更容易入睡。\n4. 避免饮用含有咖啡因的饮料:咖啡因是一种刺激性物质,会影响你的睡眠质量。尽量避免在睡前饮用含有咖啡因的饮料,例如咖啡,茶和可乐。\n5. 避免在床上做与睡眠无关的事情:在床上做些与睡眠无关的事情,例如看电影,玩游戏或工作等,可能会干扰你的睡眠。\n6. 尝试呼吸技巧:深呼吸是一种放松技巧,可以帮助你缓解紧张和焦虑,使你更容易入睡。试着慢慢吸气,保持几秒钟,然后缓慢呼气。\n\n如果这些方法无法帮助你入睡,你可以考虑咨询医生或睡眠专家,寻求进一步的建议。"}]}
```
或者
```json
{"id": 1, "conversations": [{"from": "system", "value": "You are a helpful assistant."}, {"from": "user", "value": "Answer the following questions as best you can. You have access to the following tools:\n\nquark_search: Call this tool to interact with the 夸克搜索 API. What is the 夸克搜索 API useful for? 夸克搜索是一个通用搜索引擎，可用于访问互联网、查询百科知识、了解时事新闻等。 Parameters: [{\"name\": \"search_query\", \"description\": \"搜索关键词或短语\", \"required\": true, \"schema\": {\"type\": \"string\"}}] Format the arguments as a JSON object.\n\nimage_gen: Call this tool to interact with the 通义万相 API. What is the 通义万相 API useful for? 通义万相是一个AI绘画（图像生成）服务，输入文本描述，返回根据文本作画得到的图片的URL Parameters: [{\"name\": \"query\", \"description\": \"中文关键词，描述了希望图像具有什么内容\", \"required\": true, \"schema\": {\"type\": \"string\"}}] Format the arguments as a JSON object.\n\nUse the following format:\n\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [quark_search,image_gen]\nAction Input: the input to the action\nObservation: the result of the action\n... (this Thought/Action/Action Input/Observation can be repeated zero or more times)\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n\nBegin!\n\nQuestion: 现在给我画个五彩斑斓的黑"}, {"from": "assistant", "value": "\nThought: 我应该使用通义万相API来生成一张五彩斑斓的黑的图片。\nAction: image_gen\nAction Input: {\"query\": \"五彩斑斓的黑\"}\n "}, {"from": "observation", "value": "Observation: \n{\"status_code\": 200, \"request_id\": \"3d894da2-0e26-9b7c-bd90-102e5250ae03\", \"code\": null, \"message\": \"\", \"output\": {\"task_id\": \"2befaa09-a8b3-4740-ada9-4d00c2758b05\", \"task_status\": \"SUCCEEDED\", \"results\": [{\"url\": \"https://dashscope-result-sh.oss-cn-shanghai.aliyuncs.com/1e5e2015/20230801/1509/6b26bb83-469e-4c70-bff4-a9edd1e584f3-1.png\"}], \"task_metrics\": {\"TOTAL\": 1, \"SUCCEEDED\": 1, \"FAILED\": 0}}, \"usage\": {\"image_count\": 1}}\n"}, {"from": "assistant", "value": "\nThought: 我已经成功使用通义万相API生成了一张五彩斑斓的黑的图片。\nFinal Answer: 我已经成功使用通义万相API生成了一张五彩斑斓的黑的图片https://dashscope-result-sh.oss-cn-shanghai.aliyuncs.com/1e5e2015/20230801/1509/6b26bb83-469e-4c70-bff4-a9edd1e584f3-1.png。\n "}]}
{"id": 2, "conversations": [{"from": "system", "value": "You are a helpful assistant."}, {"from": "user", "value": "从南京到上海的路线"}, {"from": "assistant", "value": "你好，南京到上海的路线如下：\n1. 南京到上海，可以乘坐南京地铁1号线，在南京站乘坐轨道交通1号线。\n2. 南京到浦东机场，可以搭乘上海地铁1号，在陆家嘴站乘坐地铁1线，在浦东国际机场站乘坐机场快线，前往上海浦东国际机场。\n3. 上海到南京，可以换乘上海地铁2号线，从南京站换乘地铁2线，再从南京南站换乘地铁1路，然后到达上海站"}]}
{"id": 3, "conversations": [{"from": "system", "value": "You are a helpful assistant."}, {"from": "user", "value": "写一个诗歌，关于冬天"}, {"from": "assistant", "value": "冬夜寂静冷，\n云在天边飘，\n冰封白雪上， \n寒冷像一场雪。\n \n雪花融化成冰，\n像那雪花飘洒，\n在寒冷的冬天，\n感受春天的喜悦。\n 冬日里，\n风雪渐消，\n一片寂静，\n把快乐和温暖带回家。"}]}
{"id": 4, "conversations": [{"from": "system", "value": "You are a helpful assistant."}, {"from": "user", "value": "晚上睡不着应该怎么办"}, {"from": "assistant", "value": "晚上睡不着可能会让你感到焦虑或不舒服,但以下是一些可以帮助你入睡的方法:\n\n1. 制定规律的睡眠时间表:保持规律的睡眠时间表可以帮助你建立健康的睡眠习惯,使你更容易入睡。尽量在每天的相同时间上床,并在同一时间起床。\n2. 创造一个舒适的睡眠环境:确保睡眠环境舒适,安静,黑暗且温度适宜。可以使用舒适的床上用品,并保持房间通风。\n3. 放松身心:在睡前做些放松的活动,例如泡个热水澡,听些轻柔的音乐,阅读一些有趣的书籍等,有助于缓解紧张和焦虑,使你更容易入睡。\n4. 避免饮用含有咖啡因的饮料:咖啡因是一种刺激性物质,会影响你的睡眠质量。尽量避免在睡前饮用含有咖啡因的饮料,例如咖啡,茶和可乐。\n5. 避免在床上做与睡眠无关的事情:在床上做些与睡眠无关的事情,例如看电影,玩游戏或工作等,可能会干扰你的睡眠。\n6. 尝试呼吸技巧:深呼吸是一种放松技巧,可以帮助你缓解紧张和焦虑,使你更容易入睡。试着慢慢吸气,保持几秒钟,然后缓慢呼气。\n\n如果这些方法无法帮助你入睡,你可以考虑咨询医生或睡眠专家,寻求进一步的建议。"}]}
```

## infer
# infer.py 推理预训练模型
# infer_finetuning.py 推理微调模型
# infer_lora_finetuning.py 推理lora微调模型
python infer.py

| **量化等级** | **最低 GPU 显存** |
| -------------- | ----------------- |
| FP16（无量化） | 13 GB |
| INT8 | 10 GB |
| INT4 | 6 GB |

![inference](assets/1.png)

## training
```text
# 制作数据
cd scripts
bash train_full.sh -m dataset
or
bash train_lora.sh -m dataset
or
bash train_ptv2.sh -m dataset

注: num_process_worker 为多进程制作数据，如果数据量较大，适当调大至cpu数量
dataHelper.make_dataset_with_args(data_args.train_file,mixed_data=False, shuffle=True,mode='train',num_process_worker=0)

# 全参数训练
bash train_full.sh -m train

# lora adalora ia3
bash train_lora.sh -m train

# ptv2
bash train_ptv2.sh -m train
```

## aigc-serving

部署qwen之后，可测试工具函数
- [quad_calculator.py](https://github.com/ssbuild/aigc_serving/blob/main/tests/quad_calculator.py)

## 训练参数
[训练参数](args.MD)

## 友情链接

- [pytorch-task-example](https://github.com/ssbuild/pytorch-task-example)
- [moss_finetuning](https://github.com/ssbuild/chatmoss_finetuning)
- [chatglm_finetuning](https://github.com/ssbuild/chatglm_finetuning)
- [chatglm2_finetuning](https://github.com/ssbuild/chatglm2_finetuning)
- [chatglm3_finetuning](https://github.com/ssbuild/chatglm3_finetuning)
- [t5_finetuning](https://github.com/ssbuild/t5_finetuning)
- [llm_finetuning](https://github.com/ssbuild/llm_finetuning)
- [llm_rlhf](https://github.com/ssbuild/llm_rlhf)
- [chatglm_rlhf](https://github.com/ssbuild/chatglm_rlhf)
- [t5_rlhf](https://github.com/ssbuild/t5_rlhf)
- [rwkv_finetuning](https://github.com/ssbuild/rwkv_finetuning)
- [baichuan_finetuning](https://github.com/ssbuild/baichuan_finetuning)
- [xverse_finetuning](https://github.com/ssbuild/xverse_finetuning)
- [internlm_finetuning](https://github.com/ssbuild/internlm_finetuning)
- [qwen_finetuning](https://github.com/ssbuild/qwen_finetuning)
- [skywork_finetuning](https://github.com/ssbuild/skywork_finetuning)
- [bluelm_finetuning](https://github.com/ssbuild/bluelm_finetuning)
- [yi_finetuning](https://github.com/ssbuild/yi_finetuning)

##
纯粹而干净的代码

## Reference
https://github.com/QwenLM/Qwen-7B

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=ssbuild/qwen_finetuning&type=Date)](https://star-history.com/#ssbuild/qwen_finetuning&Date)