Training & fine-tuning
PEFT
Separates compact trainable adapters from base-model weights and integrates them into existing training stacks.
Overview
Research summary
PEFT implements parameter-efficient methods that adapt pretrained models without updating every base-model parameter. Developers wrap a model with a method-specific configuration, train the selected parameters and save or reload the resulting adapter. The library integrates with Transformers, Diffusers and Accelerate, supporting both model adaptation and use of trained adapters during inference. Its main role is the adapter layer within a training stack; it does not provide the underlying pretrained model or independently define that model’s licensing.
Repository summary
- Stars
- 21,747
- 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 PEFT.
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
- 21,747
- 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 5
- https://huggingface.co/docs/peft Project page · Documentation
- https://github.com/huggingface/peft Linked repository · Research reference
- https://api.github.com/repos/huggingface/peft Research reference
- https://github.com/huggingface/peft/blob/main/README.md Research reference
- https://github.com/huggingface/peft/blob/main/LICENSE Research reference
Research metadata
- Research date
- 2026-10-02
- Catalogue snapshot
- 2026-10-06
Community & social 1 channels
Communities
- GitHub Discussionsgithub.com/huggingface/peft/discussionsOfficial
Link details for GitHub Discussions
- Last checked
Related tools
Editorially linked entries to explore alongside PEFT. This is not a ranking.
