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<h3> Qwen-WisdomVast (千问-智瀚)</h3>
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## 介绍
**Qwen-WisdomVast****以Qwen1.5-7B为底座**,使用 [DORA](https://arxiv.org/pdf/2402.09353.pdf) + [LORA+](https://arxiv.org/pdf/2402.12354.pdf) 的训练方法,在100w高质量中文多轮SFT数据 + 20w英文多轮SFT数据 + 2000单轮自我认知数据训练而来的大模型,**数学能力**相比Qwen1.5-7B-Chat**提升了5.16%**,在**HumanEval**数据集上相比Qwen1.5-7B-Chat**提升了12.8**,在**MBPP**数据集上**提升了11.6%**,在**BBH** 数据集上 **提升了12.44%** ,全部评测表现见下表。
**Github:**[https://github.com/seanzhang-zhichen/Qwen-WisdomVast](https://github.com/seanzhang-zhichen/Qwen-WisdomVast)
![DEMO](./images/image.png)
## 评测表现
| Model | MMLU | C-Eval | GSM8K | MATH | HumanEval | MBPP | BBH |
|-------------------|-------|--------|-------|-------|-----------|-------|-------|
| **Qwen1.5-7B-Chat** | 60.88 | 70.18 | 54.13 | 7.96 | 31.10 | 15.00 | 31.67 |
| **Qwen-WisdomVast** | 57.09 | **70.82** | 51.93 | **13.12** | **43.90** | **26.60** | **44.11** |
说明:
由于官方并未公布Qwen1.5-7B-Chat的评测表现,所以我们自己使用[opencompass](https://github.com/open-compass/opencompass)测试得到以上结果
Qwen-WisdomVast使用和Qwen1.5-7B-Chat一样的参数进行测试
## 模型下载
| Model | Download |
|:-------------------:|:-----------:|
| Qwen1.5-7B |[ 🤗 HuggingFace](https://huggingface.co/Qwen/Qwen1.5-7B) [ 🤖 ModelScope](https://modelscope.cn/models/qwen/Qwen1.5-7B)|
| Qwen-WisdomVast-Lora |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Qwen-WisdomVast-Lora) [ 🤖 ModelScope](https://modelscope.cn/models/seanzhang/Qwen-WisdomVast-Lora)|
| Qwen-WisdomVast (合并好的模型) |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Qwen-WisdomVast) [ 🤖 ModelScope](https://modelscope.cn/models/seanzhang/Qwen-WisdomVast)|
## 合并LORA模型(可跳过)
1、下载 [Qwen1.5-7B](https://modelscope.cn/models/qwen/Qwen1.5-7B)
```bash
git clone https://www.modelscope.cn/qwen/Qwen1.5-7B.git
```
2、下载[Qwen-WisdomVast-Lora](https://www.modelscope.cn/models/seanzhang/Qwen-WisdomVast-Lora)
**From ModelScope**
```bash
git lfs install
git clone https://www.modelscope.cn/seanzhang/Qwen-WisdomVast-Lora.git
```
**From HuggingFace**
```bash
git lfs install
git clone https://huggingface.co/zhichen/Qwen-WisdomVast-Lora
```
3、合并模型
```bash
python merge_lora.py \
--base_model path/to/qwen/Qwen1.5-7B \
--lora_model path/to/lora/Qwen-WisdomVast-Lora \
--output_dir ./Qwen-WisdomVast
```
## 下载 Qwen-WisdomVast(合并好的模型)
**From ModelScope**
```bash
git lfs install
git clone https://www.modelscope.cn/seanzhang/Qwen-WisdomVast.git
```
**From HuggingFace**
```bash
git lfs install
git clone https://huggingface.co/zhichen/Qwen-WisdomVast
```
## 命令行推理
```bash
python cli_demo.py --model_path ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
```
## web 推理
```bash
python web_demo.py --model_path ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
```
## vllm web 推理
1、使用[vllm](https://github.com/vllm-project/vllm)部署模型
```bash
python -m vllm.entrypoints.openai.api_server --served-model-name Qwen-WisdomVast --model ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
```
2、在命令行执行
```bash
python vllm_web_demo.py --model Qwen-WisdomVast
```
## 复现测试结果
1、使用[vllm](https://github.com/vllm-project/vllm)部署`openai api server`
部署命令:
```bash
python -m vllm.entrypoints.openai.api_server --served-model-name Qwen-WisdomVast --model ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
```
2、使用[opencompass](https://github.com/open-compass/opencompass)框架进行测试
参考:[使用opencompass验证模型效果](https://blog.csdn.net/qq_44193969/article/details/134979054)
按照以上文章修改好后,将`eval_qwen_wisdomvast.py`文件到 `opencompass/configs`文件夹下
3、执行测试脚本
```bash
python run.py configs/eval_qwen_wisdomvast.py -w outputs/Qwen-WisdomVast
```
## LICENSE
本项目仅可应用于研究目的,项目开发者不承担任何因使用本项目(包含但不限于数据、模型、代码等)导致的危害或损失。详细请参考[免责声明](https://github.com/seanzhang-zhichen/Qwen-WisdomVast/blob/main/DISCLAIMER)。
Qwen-WisdomVast项目代码的授权协议为 [The Apache License 2.0](.//LICENSE),代码可免费用做商业用途,模型权重和数据只能用于研究目的。请在产品说明中附加Qwen-WisdomVast的链接和授权协议。
## Citation
如果你在研究中使用了Qwen-WisdomVast,请按如下格式引用:
```latex
@misc{Qwen-WisdomVast,
title={Qwen-WisdomVast},
author={Zhichen Zhang, Weihan Huang},
year={2024},
howpublished={\url{https://github.com/seanzhang-zhichen/Qwen-WisdomVast}},
}
```
## Acknowledgement
[QwenLM/Qwen1.5](https://github.com/QwenLM/Qwen1.5)
<br>
[hiyouga/LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
<br>
[shibing624/MedicalGPT](https://github.com/shibing624/MedicalGPT)
<br>
[modelscope/swift](https://github.com/modelscope/swift)
## Star History
[![Star History Chart](https://api.star-history.com/svg?repos=seanzhang-zhichen/Qwen-WisdomVast&type=Date)](https://star-history.com/#seanzhang-zhichen/Qwen-WisdomVast&Date)