add readme

README.md

@@ -1,3 +1,154 @@
----
-license: apache-2.0
----
+<p align="left">
+    中文</a>&nbsp ｜ &nbsp<a href="README.md">English</a>
+</p>
+<br><br>
+
+<p align="center">
+<a href='https://huggingface.co/spaces/zhichen'>
+<img src='./images/logo.png'>
+</a>
+</p>
+
+<div align="center">
+  <p align="center">
+    <h3> Llama3-Chinese </h3>
+
+<p align="center">
+      <a href='https://huggingface.co/zhichen'>
+        <img src='https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Llama3%20Chinese-yellow'>
+      </a>
+      <a href='https://modelscope.cn/profile/seanzhang'>
+        <img src='https://img.shields.io/badge/🤖 ModelScope-Llama3%20Chinese-blue'>
+      </a>
+      <br>
+      <a href=href="https://github.com/seanzhang-zhichen/llama3-chinese/stargazers">
+        <img src="https://img.shields.io/github/stars/seanzhang-zhichen/llama3-chinese?color=ccf">
+      </a>
+      <a href="https://github.com/seanzhang-zhichen/llama3-chinese/blob/main/LICENSE">
+        <img alt="GitHub Contributors" src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" />
+      </a>
+</p>
+</div>
+
+
+## 介绍
+
+**Llama3-Chinese**是**以Meta-Llama-3-8B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50w高质量中文多轮SFT数据 + 10w英文多轮SFT数据 + 2000单轮自我认知数据训练而来的大模型。
+
+**Github:** [https://github.com/seanzhang-zhichen/llama3-chinese](https://github.com/seanzhang-zhichen/llama3-chinese)
+
+![DEMO](./images/vllm_web_demo.png)
+
+
+## 模型下载
+
+| Model             | Download  |
+|:-------------------:|:-----------:|
+| Meta-Llama-3-8B        |[ 🤗 HuggingFace](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [  🤖 ModelScope](https://modelscope.cn/models/LLM-Research/Meta-Llama-3-8B)|
+| Llama3-Chinese-Lora           |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Llama3-Chinese-Lora) [  🤖 ModelScope](https://modelscope.cn/models/seanzhang/Llama3-Chinese-Lora)|
+| Llama3-Chinese (合并好的模型)           |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Llama3-Chinese) [  🤖 ModelScope](https://modelscope.cn/models/seanzhang/Llama3-Chinese)|
+
+
+
+## 合并LORA模型（可跳过）
+
+1、下载 [Meta-Llama-3-8B](https://modelscope.cn/models/LLM-Research/Meta-Llama-3-8B)
+
+```bash
+git clone https://www.modelscope.cn/LLM-Research/Meta-Llama-3-8B.git
+```
+
+2、下载[Llama3-Chinese-Lora](https://www.modelscope.cn/models/seanzhang/Llama3-Chinese-Lora)
+
+**From ModelScope**
+```bash
+git lfs install
+git clone https://www.modelscope.cn/seanzhang/Llama3-Chinese-Lora.git
+```
+
+**From HuggingFace**
+```bash
+git lfs install
+git clone https://huggingface.co/zhichen/Llama3-Chinese-Lora
+```
+
+3、合并模型
+
+```bash
+python merge_lora.py \
+    --base_model path/to/Meta-Llama-3-8B \
+    --lora_model path/to/lora/Llama3-Chinese-Lora  \
+    --output_dir ./Llama3-Chinese
+```
+
+## 下载 Llama3-Chinese（合并好的模型）
+
+**From ModelScope**
+```bash
+git lfs install
+git clone https://www.modelscope.cn/seanzhang/Llama3-Chinese.git
+```
+
+**From HuggingFace**
+```bash
+git lfs install
+git clone https://huggingface.co/zhichen/Llama3-Chinese
+```
+
+
+
+
+## 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 Llama3-Chinese --model ./Llama3-Chinese(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 Llama3-Chinese
+```
+
+
+
+
+## 训练数据集
+
+[匠数科技大模型sft数据集](https://modelscope.cn/datasets/deepctrl/deepctrl-sft-data)
+
+
+## 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/Llama3-Chinese/blob/main/DISCLAIMER)。
+
+Llama3-Chinese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Llama3-Chinese的链接和授权协议。
+
+## Citation
+
+如果你在研究中使用了Llama3-Chinese，请按如下格式引用：
+
+```latex
+@misc{Llama3-Chinese,
+  title={Llama3-Chinese},
+  author={Zhichen Zhang},
+  year={2024},
+  howpublished={\url{https://github.com/seanzhang-zhichen/llama3-chinese}},
+}
+```
+
+
+## Acknowledgement
+
+[meta-llama/llama3](https://github.com/meta-llama/llama3)
+<br>
+[hiyouga/LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
+
+
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=seanzhang-zhichen/Llama3-Chinese&type=Date)](https://star-history.com/#seanzhang-zhichen/Llama3-Chinese&Date)
+

README_CN.md

@@ -0,0 +1,154 @@
+<p align="left">
+    中文</a>&nbsp ｜ &nbsp<a href="README.md">English</a>
+</p>
+<br><br>
+
+<p align="center">
+<a href='https://huggingface.co/spaces/zhichen'>
+<img src='./images/logo.png'>
+</a>
+</p>
+
+<div align="center">
+  <p align="center">
+    <h3> Llama3-Chinese </h3>
+
+<p align="center">
+      <a href='https://huggingface.co/zhichen'>
+        <img src='https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Llama3%20Chinese-yellow'>
+      </a>
+      <a href='https://modelscope.cn/profile/seanzhang'>
+        <img src='https://img.shields.io/badge/🤖 ModelScope-Llama3%20Chinese-blue'>
+      </a>
+      <br>
+      <a href=href="https://github.com/seanzhang-zhichen/llama3-chinese/stargazers">
+        <img src="https://img.shields.io/github/stars/seanzhang-zhichen/llama3-chinese?color=ccf">
+      </a>
+      <a href="https://github.com/seanzhang-zhichen/llama3-chinese/blob/main/LICENSE">
+        <img alt="GitHub Contributors" src="https://img.shields.io/badge/license-Apache%202.0-blue.svg" />
+      </a>
+</p>
+</div>
+
+
+## 介绍
+
+**Llama3-Chinese**是**以Meta-Llama-3-8B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50w高质量中文多轮SFT数据 + 10w英文多轮SFT数据 + 2000单轮自我认知数据训练而来的大模型。
+
+**Github:** [https://github.com/seanzhang-zhichen/llama3-chinese](https://github.com/seanzhang-zhichen/llama3-chinese)
+
+![DEMO](./images/vllm_web_demo.png)
+
+
+## 模型下载
+
+| Model             | Download  |
+|:-------------------:|:-----------:|
+| Meta-Llama-3-8B        |[ 🤗 HuggingFace](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [  🤖 ModelScope](https://modelscope.cn/models/LLM-Research/Meta-Llama-3-8B)|
+| Llama3-Chinese-Lora           |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Llama3-Chinese-Lora) [  🤖 ModelScope](https://modelscope.cn/models/seanzhang/Llama3-Chinese-Lora)|
+| Llama3-Chinese (合并好的模型)           |[ 🤗 HuggingFace](https://huggingface.co/zhichen/Llama3-Chinese) [  🤖 ModelScope](https://modelscope.cn/models/seanzhang/Llama3-Chinese)|
+
+
+
+## 合并LORA模型（可跳过）
+
+1、下载 [Meta-Llama-3-8B](https://modelscope.cn/models/LLM-Research/Meta-Llama-3-8B)
+
+```bash
+git clone https://www.modelscope.cn/LLM-Research/Meta-Llama-3-8B.git
+```
+
+2、下载[Llama3-Chinese-Lora](https://www.modelscope.cn/models/seanzhang/Llama3-Chinese-Lora)
+
+**From ModelScope**
+```bash
+git lfs install
+git clone https://www.modelscope.cn/seanzhang/Llama3-Chinese-Lora.git
+```
+
+**From HuggingFace**
+```bash
+git lfs install
+git clone https://huggingface.co/zhichen/Llama3-Chinese-Lora
+```
+
+3、合并模型
+
+```bash
+python merge_lora.py \
+    --base_model path/to/Meta-Llama-3-8B \
+    --lora_model path/to/lora/Llama3-Chinese-Lora  \
+    --output_dir ./Llama3-Chinese
+```
+
+## 下载 Llama3-Chinese（合并好的模型）
+
+**From ModelScope**
+```bash
+git lfs install
+git clone https://www.modelscope.cn/seanzhang/Llama3-Chinese.git
+```
+
+**From HuggingFace**
+```bash
+git lfs install
+git clone https://huggingface.co/zhichen/Llama3-Chinese
+```
+
+
+
+
+## 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 Llama3-Chinese --model ./Llama3-Chinese(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 Llama3-Chinese
+```
+
+
+
+
+## 训练数据集
+
+[匠数科技大模型sft数据集](https://modelscope.cn/datasets/deepctrl/deepctrl-sft-data)
+
+
+## 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/Llama3-Chinese/blob/main/DISCLAIMER)。
+
+Llama3-Chinese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Llama3-Chinese的链接和授权协议。
+
+## Citation
+
+如果你在研究中使用了Llama3-Chinese，请按如下格式引用：
+
+```latex
+@misc{Llama3-Chinese,
+  title={Llama3-Chinese},
+  author={Zhichen Zhang},
+  year={2024},
+  howpublished={\url{https://github.com/seanzhang-zhichen/llama3-chinese}},
+}
+```
+
+
+## Acknowledgement
+
+[meta-llama/llama3](https://github.com/meta-llama/llama3)
+<br>
+[hiyouga/LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory)
+
+
+
+## Star History
+
+[![Star History Chart](https://api.star-history.com/svg?repos=seanzhang-zhichen/Llama3-Chinese&type=Date)](https://star-history.com/#seanzhang-zhichen/Llama3-Chinese&Date)
+