Training & fine-tuning
TRL
Offers task-specific post-training trainers that compose with Transformers, Accelerate and PEFT.
Overview
Research summary
TRL provides trainer classes for post-training foundation models within the Hugging Face ecosystem. Its documented methods include supervised fine-tuning, direct preference optimization, group-relative policy optimization and reward-model training. It builds on Transformers and integrates Accelerate for distributed execution, PEFT for adapter training and optional optimized backends. Developers can use Python trainer APIs or command-line entry points with their own datasets. The library supplies training algorithms and integration code rather than a hosted training service.
Repository summary
- Stars
- 19,433
- Open issues
- Unavailable
- Last push
- 2026-10-01
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services unknown
Whether the provider offers paid products or services has not been established.
Licence scope
Implementation
Recorded implementation details and interfaces for TRL.
Implementation details
Python library and supporting tools
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- 19,433
- Open issues
- Unavailable
- Last push
- 2026-10-01
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
- Stars source
- Recorded fallback
- Last push source
- Recorded fallback
Documentation
Recorded references and research provenance for this entry.
Recorded sources 6
- https://huggingface.co/docs/trl Project page · Documentation
- https://github.com/huggingface/trl Linked repository · Research reference
- https://api.github.com/repos/huggingface/trl Research reference
- https://github.com/huggingface/trl/blob/main/README.md Research reference
- https://github.com/huggingface/trl/blob/main/LICENSE Research reference
- http://hf.co/docs/trl Research reference
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06
Community & social 1 channels
Communities
- GitHub Discussionsgithub.com/huggingface/trl/discussionsOfficial
Link details for GitHub Discussions
- Last checked
Related tools
Editorially linked entries to explore alongside TRL. This is not a ranking.
