minimind/README.md

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<h3>"The Greatest Path is the Simplest"</h3>
<a href="https://github.com/jingyaogong/minimind">🔗MiniMind Github Repo🔗</a>
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* This open-source project aims to train a miniature language model **MiniMind** from scratch, with a size of just 26MB.
* **MiniMind** is extremely lightweight, approximately 1/7000 the size of GPT-3, designed to enable fast
inference and even training on CPUs.
* **MiniMind** is an improvement on the DeepSeek-V2 and Llama3 architectures. The project includes all stages of data
processing, pretraining, SFT, and DPO, and features a Mixture of Experts (MoE) model.
* This is not only the implementation of an open-source model, but also a tutorial for getting started with large
language models (LLMs).
* We hope that this project serves as a stepping stone for researchers and developers, providing an introductory example
to help them quickly get started and foster more exploration and innovation in the LLM field.
> To avoid any misunderstanding, "fastest 3 hours" refers to the requirement of using hardware with higher
specifications than the author's setup. Detailed specifications will be provided below.
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<img src="./images/streamlit.gif"></img>
<a href="https://www.modelscope.cn/studios/gongjy/minimind">ModelScope Online</a> |
<a href="https://www.bilibili.com/video/BV12dHPeqE72/?share_source=copy_web&vd_source=670c2504f88726f8cf4a21ef6147c0e8">Bilibili Video Link</a>
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