Overview
A lightweight implementation for exploring small language model pretraining and fine-tuning. The repository is maintained under jingyaogong on GitHub. Its primary language is Python. See the [project README](https://github.com/jingyaogong/minimind#readme) for the supported workflows.
Key features
- A lightweight implementation for exploring small language model pretraining and fine-tuning.
Requirements, installation and quick start
Follow the repository quickstart to install dependencies and obtain the model or training data required by the selected example.
[Read the upstream installation and quickstart instructions](https://github.com/jingyaogong/minimind#readme).
[Read the upstream installation and quickstart instructions](https://github.com/jingyaogong/minimind#readme).
Usage
Run a small inference or training example first, then adjust the documented configuration for your hardware and dataset.
[Usage examples and configuration reference](https://github.com/jingyaogong/minimind#readme).
[Usage examples and configuration reference](https://github.com/jingyaogong/minimind#readme).
Model compatibility and use cases
Model compatibility is not stated in the repository metadata.
License and risk notes
GitHub reports Apache-2.0 for this repository. Review the upstream license file; model weights, datasets and dependencies may have separate terms.
Source review 2026-09-05: GitHub search metadata and repository README. No runtime benchmark performed. License metadata: Apache-2.0.
Release and maintenance
[View upstream releases](https://github.com/jingyaogong/minimind/releases).