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Model: seanzhang/Qwen-WisdomVast Source: Original Platform
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<p align="center">
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<a href='https://huggingface.co/spaces/zhichen'>
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<img src='./images/logo.png'>
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</a>
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</p>
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<div align="center">
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<p align="center">
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<h3> Qwen-WisdomVast (千问-智瀚)</h3>
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<p align="center">
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<a href='https://huggingface.co/zhichen'>
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<img src='https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Qwen%20WisdomVast-yellow'>
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</a>
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<a href='https://modelscope.cn/profile/seanzhang'>
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<img src='https://img.shields.io/badge/🤖 ModelScope-Qwen%20WisdomVast-blue'>
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</a>
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<br>
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<a href=href="https://github.com/seanzhang-zhichen/Qwen-WisdomVast/stargazers">
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<img src="https://img.shields.io/github/stars/seanzhang-zhichen/Qwen-WisdomVast?color=ccf">
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</a>
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<a href="https://github.com/seanzhang-zhichen/Qwen-WisdomVast/blob/main/LICENSE">
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<img alt="GitHub Contributors" src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" />
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</a>
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</p>
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</div>
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## 介绍
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**Qwen-WisdomVast**是**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。
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**Github：**[https://github.com/seanzhang-zhichen/Qwen-WisdomVast](https://github.com/seanzhang-zhichen/Qwen-WisdomVast)
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## 评测表现
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| Model | MMLU | C-Eval | GSM8K | MATH | HumanEval | MBPP | BBH |
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|-------------------|-------|--------|-------|-------|-----------|-------|-------|
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| **Qwen1.5-7B-Chat** | 60.88 | 70.18 | 54.13 | 7.96 | 31.10 | 15.00 | 31.67 |
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| **Qwen-WisdomVast** | 57.09 | **70.82** | 51.93 | **13.12** | **43.90** | **26.60** | **44.11** |
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说明：
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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
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Qwen-WisdomVast使用和Qwen1.5-7B-Chat一样的参数进行测试
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## 模型下载
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| Model | Download |
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|:-------------------:|:-----------:|
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| Qwen1.5-7B |[ 🤗 HuggingFace](https://huggingface.co/Qwen/Qwen1.5-7B) [ 🤖 ModelScope](https://modelscope.cn/models/qwen/Qwen1.5-7B)|
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| Qwen-WisdomVast-Lora |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Qwen-WisdomVast-Lora) [ 🤖 ModelScope](https://modelscope.cn/models/seanzhang/Qwen-WisdomVast-Lora)|
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| Qwen-WisdomVast (合并好的模型) |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Qwen-WisdomVast) [ 🤖 ModelScope](https://modelscope.cn/models/seanzhang/Qwen-WisdomVast)|
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## 合并LORA模型（可跳过）
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1、下载 [Qwen1.5-7B](https://modelscope.cn/models/qwen/Qwen1.5-7B)
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```bash
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git clone https://www.modelscope.cn/qwen/Qwen1.5-7B.git
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```
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2、下载[Qwen-WisdomVast-Lora](https://www.modelscope.cn/models/seanzhang/Qwen-WisdomVast-Lora)
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**From ModelScope**
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```bash
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git lfs install
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git clone https://www.modelscope.cn/seanzhang/Qwen-WisdomVast-Lora.git
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```
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**From HuggingFace**
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```bash
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git lfs install
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git clone https://huggingface.co/zhichen/Qwen-WisdomVast-Lora
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```
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3、合并模型
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```bash
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python merge_lora.py \
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--base_model path/to/qwen/Qwen1.5-7B \
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--lora_model path/to/lora/Qwen-WisdomVast-Lora \
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--output_dir ./Qwen-WisdomVast
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```
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## 下载 Qwen-WisdomVast（合并好的模型）
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**From ModelScope**
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```bash
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git lfs install
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git clone https://www.modelscope.cn/seanzhang/Qwen-WisdomVast.git
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```
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**From HuggingFace**
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```bash
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git lfs install
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git clone https://huggingface.co/zhichen/Qwen-WisdomVast
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```
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## 命令行推理
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```bash
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python cli_demo.py --model_path ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
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```
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## web 推理
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```bash
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python web_demo.py --model_path ./Qwen-WisdomVast(换成你自己的合并后的模型路径)
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```
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## vllm web 推理
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1、使用[vllm](https://github.com/vllm-project/vllm)部署模型
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```bash
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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)
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```
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2、在命令行执行
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```bash
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python vllm_web_demo.py --model Qwen-WisdomVast
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```
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## 复现测试结果
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1、使用[vllm](https://github.com/vllm-project/vllm)部署`openai api server`
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部署命令:
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```bash
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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)
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```
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2、使用[opencompass](https://github.com/open-compass/opencompass)框架进行测试
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参考：[使用opencompass验证模型效果](https://blog.csdn.net/qq_44193969/article/details/134979054)
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按照以上文章修改好后，将`eval_qwen_wisdomvast.py`文件到 `opencompass/configs`文件夹下
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3、执行测试脚本
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```bash
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python run.py configs/eval_qwen_wisdomvast.py -w outputs/Qwen-WisdomVast
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```
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## LICENSE
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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)。
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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。
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## Citation
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如果你在研究中使用了Qwen-WisdomVast，请按如下格式引用：
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```latex
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@misc{Qwen-WisdomVast,
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title={Qwen-WisdomVast},
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author={Zhichen Zhang, Weihan Huang},
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year={2024},
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howpublished={\url{https://github.com/seanzhang-zhichen/Qwen-WisdomVast}},
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}
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```
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## Acknowledgement
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[QwenLM/Qwen1.5](https://github.com/QwenLM/Qwen1.5)
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<br>
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[hiyouga/LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
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||||
<br>
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||||
[shibing624/MedicalGPT](https://github.com/shibing624/MedicalGPT)
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<br>
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[modelscope/swift](https://github.com/modelscope/swift)
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## Star History
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[](https://star-history.com/#seanzhang-zhichen/Qwen-WisdomVast&Date)
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||||
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|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
20
special_tokens_map.json
Normal file
20
special_tokens_map.json
Normal file
@@ -0,0 +1,20 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
44
tokenizer_config.json
Normal file
44
tokenizer_config.json
Normal file
@@ -0,0 +1,44 @@
|
||||
{
|
||||
"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
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>"
|
||||
],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% set system_message = 'You are a helpful assistant.' %}{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ '<|im_start|>system\\n' + system_message + '<|im_end|>\\n' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|im_start|>user\\n' + content + '<|im_end|>\\n<|im_start|>assistant\\n' }}{% elif message['role'] == 'assistant' %}{{ content + '<|im_end|>' + '\\n' }}{% endif %}{% endfor %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
151645
vocab.json
Normal file
151645
vocab.json
Normal file
File diff suppressed because it is too large
Load Diff
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