LLM & Model Fondasi

minimind

jingyaogong/minimind

A lightweight implementation for exploring small language model pretraining and fine-tuning.

★ 58,6KBintang
⑂ 7,6KFork
60Isu terbuka
PythonBahasa
Apache-2.0Lisensi
Q90Skor editorial

Ringkasan

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.

Fitur utama

  • A lightweight implementation for exploring small language model pretraining and fine-tuning.

Persyaratan, instalasi, dan mulai cepat

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).

Penggunaan

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).

Kompatibilitas model dan kasus penggunaan

Kompatibilitas model tidak tercantum dalam metadata repositori.

Catatan lisensi dan risiko

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.

Rilis dan pemeliharaan

[View upstream releases](https://github.com/jingyaogong/minimind/releases).

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