Resumen
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.
Características principales
- A lightweight implementation for exploring small language model pretraining and fine-tuning.
Requisitos, instalación y guía rápida
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).
Uso
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).
Compatibilidad de modelos y casos de uso
La compatibilidad del modelo no se indica en los metadatos del repositorio.
Notas sobre la licencia y los riesgos
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.
Lanzamiento y mantenimiento
[View upstream releases](https://github.com/jingyaogong/minimind/releases).