minimind
MiniMind is an open-source project for training a small language model from scratch and studying the LLM pipeline. It helps learners explore how models work through hands-on training and fine-tuning.
Share on XLicense: Apache-2.0
Overview
MiniMind is an open-source project for building and training small language models from scratch, intended to make LLM internals easier to study without relying on high-level training abstractions. It provides PyTorch implementations of model structures and a training path spanning pretraining, supervised fine-tuning, LoRA, preference optimization, tool use, and distillation. Users can follow the code, train on personal GPU hardware, evaluate models, and serve them through a lightweight API or chat interface. The repository also includes datasets and tokenizer training code.
Key features
- PyTorch model structure and tokenizer training code
- Training workflows for pretraining, fine-tuning, LoRA, preference optimization, tool use, and distillation
- Datasets and support for model evaluation
- Lightweight API server and Streamlit chat interface
Best for
Learners and developers who want to understand LLM internals by reproducing small-model training. It is suited to experiments on personal GPU hardware.
- Upstream
- jingyaogong/minimind
- Fork on GitHub
- Guo-astro/minimind
- Upstream stars
- 64k
- Category
- AI agents and LLM tools
- License
- Apache-2.0
- Forked
- 2026-10-14
- Sync status
- In syncLast synced 2026-10-17
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