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README.md
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@ -79,16 +79,24 @@
希望此开源项目可以帮助LLM初学者快速入门！
👉**最近更新**
👉**Recent Updates**
<details close>
<summary> <b>2024-09-01 (new🎉)</b> </summary>
- 更新MiniMind-V1 (108M)模型，采用minimind_tokenizer，预训练轮次3 + SFT轮次10，更充分训练，性能更强。
<summary> <b>September 1, 2024 (new🎉)</b> </summary>
- Updated MiniMind-V1 (108M) model, using minimind_tokenizer, with 3 rounds of pre-training + 10 rounds of SFT, more thorough training, stronger performance.
- The project has been deployed to the ModelScope Creation Space, where you can experience it on this website:
- [ModelScope Online Experience](https://www.modelscope.cn/studios/gongjy/minimind)
</details>
<details close>
<summary> <b>2024-08-27</b> </summary>
- 项目首次开源
<summary> <b>August 27, 2024</b> </summary>
- Project first open-sourced
</details>
# 📌 Environment
@ -101,24 +109,44 @@
* CUDA == 12.2
* [requirements.txt](./requirements.txt)
# 📌 Start Inference
# 📌 Deployment & Inference
<div align="center" style="font-size: 1.5em; font-weight: bold;">
<img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Hugging Face Logo" style="vertical-align: middle; height: 30px;" />
Hugging Face
[MiniMind-Collection](https://huggingface.co/collections/jingyaogong/minimind-66caf8d999f5c7fa64f399e5)
[MiniMind (HuggingFace)](https://huggingface.co/collections/jingyaogong/minimind-66caf8d999f5c7fa64f399e5)
<img src="https://g.alicdn.com/sail-web/maas/1.15.0/static/modelscopeIcon.cd89353f.svg" alt="Hugging Face Logo" style="vertical-align: middle; height: 30px;" />
[MiniMind (ModelScope)](https://www.modelscope.cn/models/gongjy/MiniMind-V1)
</div>
```bash
# step 1
git clone https://huggingface.co/jingyaogong/minimind
git clone https://huggingface.co/jingyaogong/minimind-v1
```
```bash
# step 2
python 2-eval.py
```
或者启动streamlit，启动网页聊天界面
```bash
# or step 3, use streamlit
streamlit run fast_inference.py
```
![](./images/streamlit.png)
<div align="center">
项目已部署至ModelScope创空间，可以在此网站上体验：
[ModelScope在线体验](https://www.modelscope.cn/studios/gongjy/minimind)
</div>
# 📌 Quick Start

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README_en.md
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@ -101,18 +101,23 @@ These are my personal software and hardware environment configurations. Please a
* CUDA == 12.2
* [requirements.txt](./requirements.txt)
# 📌 Start Inference
# 📌 Deployment & Inference
<div align="center" style="font-size: 1.5em; font-weight: bold;">
<img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" alt="Hugging Face Logo" style="vertical-align: middle; height: 30px;" />
Hugging Face
[MiniMind-Collection](https://huggingface.co/collections/jingyaogong/minimind-66caf8d999f5c7fa64f399e5)
[MiniMind (HuggingFace)](https://huggingface.co/collections/jingyaogong/minimind-66caf8d999f5c7fa64f399e5)
<img src="https://g.alicdn.com/sail-web/maas/1.15.0/static/modelscopeIcon.cd89353f.svg" alt="Hugging Face Logo" style="vertical-align: middle; height: 30px;" />
[MiniMind (ModelScope)](https://www.modelscope.cn/models/gongjy/MiniMind-V1)
</div>
```bash
# step 1
git clone https://huggingface.co/jingyaogong/minimind
git clone https://huggingface.co/jingyaogong/minimind-v1
```
```bash
@ -120,6 +125,22 @@ git clone https://huggingface.co/jingyaogong/minimind
python 2-eval.py
```
or you can run streamlit, launch a web page to chat with minimind-v1
```bash
# or step 3, use streamlit
streamlit run fast_inference.py
```
![](./images/streamlit.png)
<div align="center">
The project has been deployed to ModelScope makerspace, where you can experience:
[ModelScope Online](https://www.modelscope.cn/studios/gongjy/minimind)
</div>
# 📌 Quick Start
*