LLMと基盤モデル

minimind

jingyaogong/minimind

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

★ 58.6Kスター
⑂ 7.6Kフォーク数
60未解決の問題
Python言語
Apache-2.0ライセンス
Q90編集部スコア

概要

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.

主な機能

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

要件、インストール、クイックスタート

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).

使用方法

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).

モデルの互換性とユースケース

リポジトリのメタデータにモデル互換性の記載がありません。

ライセンスとリスクに関する注意事項

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.

リリースとメンテナンス

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

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