54 lines
2.3 KiB
Markdown
54 lines
2.3 KiB
Markdown
# <strong>Welcome to MiniMind!</strong>
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<figure markdown>
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<figcaption><strong>"Simplicity is the ultimate sophistication"</strong></figcaption>
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</figure>
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## 📌 Introduction
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MiniMind is a super-small language model project trained completely from scratch, requiring **only $0.5 + 2 hours** to train a **26M** language model!
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- **MiniMind** series is extremely lightweight, the smallest version is **1/7000** the size of GPT-3
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- The project open-sources the minimalist structure of large models, including:
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- Mixture of Experts (MoE)
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- Dataset cleaning
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- Pretraining
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- Supervised Fine-Tuning (SFT)
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- LoRA fine-tuning
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- Direct Preference Optimization (DPO)
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- Model distillation
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- All core algorithm code is reconstructed from scratch using native PyTorch, without relying on third-party abstract interfaces
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- This is not only a full-stage open-source reproduction of large language models, but also a tutorial for getting started with LLMs
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!!! note "Training Cost"
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"2 hours" is based on NVIDIA 3090 hardware (single card) testing, "$0.5" refers to GPU server rental cost
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## ✨ Key Features
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- **Ultra-low cost**: Single 3090, 2 hours, $0.5 to train a ChatBot from scratch
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- **Complete pipeline**: Covers Tokenizer, pretraining, SFT, LoRA, DPO, distillation full process
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- **Education-friendly**: Clean code, suitable for learning LLM principles
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- **Ecosystem compatible**: Supports `transformers`, `llama.cpp`, `vllm`, `ollama` and other mainstream frameworks
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## 📊 Model List
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| Model (Size) | Inference Memory (Approx.) | Release |
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|------------|----------|---------|
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| MiniMind2-small (26M) | 0.5 GB | 2025.04.26 |
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| MiniMind2-MoE (145M) | 1.0 GB | 2025.04.26 |
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| MiniMind2 (104M) | 1.0 GB | 2025.04.26 |
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## 🚀 Quick Navigation
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- [Quick Start](quickstart.en.md) - Environment setup, model download, quick testing
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- [Model Training](training.en.md) - Pretraining, SFT, LoRA, DPO training process
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## 🔗 Related Links
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- **GitHub**: [https://github.com/jingyaogong/minimind](https://github.com/jingyaogong/minimind)
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- **HuggingFace**: [MiniMind Collection](https://huggingface.co/collections/jingyaogong/minimind-66caf8d999f5c7fa64f399e5)
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- **ModelScope**: [MiniMind Models](https://www.modelscope.cn/profile/gongjy)
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- **Online Demo**: [ModelScope Studio](https://www.modelscope.cn/studios/gongjy/MiniMind)
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