파인튜닝, 학습 및 데이터

TRL

huggingface/trl

A library for post-training transformer models with supervised fine-tuning and preference-optimization methods.

★ 19.5K별점
⑂ 3.1K포크 수
109미해결 이슈
Python언어
Apache-2.0라이선스
Q84편집 점수

개요

TRL builds on the Transformers ecosystem and provides trainers for methods such as supervised fine-tuning (SFT), direct preference optimization (DPO), and group relative policy optimization (GRPO). It supports distributed training integrations and parameter-efficient fine-tuning workflows.

주요 기능

  • SFT, DPO, GRPO and related trainers
  • Transformers ecosystem integration
  • Distributed training support
  • CLI and Python APIs

요구 사항, 설치 및 빠른 시작

Install the Python package with `pip install trl`; follow the docs for optional Accelerate, PEFT, and hardware setup.

사용 정보

Choose a trainer, prepare a compatible dataset and model, configure training arguments, then run the trainer or CLI command.

모델 호환성 및 사용 사례

Designed for transformer models in the Hugging Face ecosystem; architecture and hardware support depends on the chosen method and dependencies.

라이선스 및 위험 참고 사항

The repository declares Apache-2.0. Dataset, base-model, and hosted service terms are separate.

릴리스 및 유지 관리

See the official repository for current releases and changes.

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