LLM 및 파운데이션 모델

minimind

jingyaogong/minimind

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

★ 58.6K별점
⑂ 7.6K포크 수
60미해결 이슈
Python언어
Apache-2.0라이선스
Q90편집 점수

개요

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.

주요 기능

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

요구 사항, 설치 및 빠른 시작

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).

사용 정보

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).

모델 호환성 및 사용 사례

저장소 메타데이터에 모델 호환성이 명시되어 있지 않습니다.

라이선스 및 위험 참고 사항

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.

릴리스 및 유지 관리

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

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