Training & fine-tuning
LlamaFactory
Makes multiple model architectures and adaptation methods available through the same CLI and training UI.
Overview
Research summary
LlamaFactory provides a common workflow for adapting supported language and vision-language models through configuration files, a command-line interface or LLaMA Board. Its documented methods include continued pretraining, supervised fine-tuning, reward modeling and preference or reinforcement-learning algorithms. Full parameter training, frozen-layer training, LoRA and several quantized adapter approaches address different resource constraints. The repository combines training recipes and integration with optimization libraries; model weights and training datasets retain their own licenses and access conditions.
Repository summary
- Stars
- 75,257
- Open issues
- Unavailable
- Last push
- 2026-09-28
- 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 LlamaFactory.
Implementation details
Python implementation with an interactive application or platform integration
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- 75,257
- Open issues
- Unavailable
- Last push
- 2026-09-28
- 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://llamafactory.readthedocs.io Project page · Documentation
- https://github.com/hiyouga/LlamaFactory Linked repository · Research reference
- https://api.github.com/repos/hiyouga/LlamaFactory Research reference
- https://github.com/hiyouga/LlamaFactory/blob/main/README.md Research reference
- https://github.com/hiyouga/LlamaFactory/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/hiyouga/LlamaFactory/discussionsOfficial
Link details for GitHub Discussions
- Last checked