TRL
Model ● Covered in 4 stories + Follow
TRL is an open-source fine-tuning framework developed by Hugging Face that provides trainer APIs for adapting large language models and diffusion models. Recent developments include a delta weight synchronization method that reduces checkpoint sizes by 98-99% through sparse encoding, integration with the Unsloth optimization library to achieve 2.7x faster training speeds, and support for DDPO (Denoising Diffusion Policy Optimization) to align diffusion model outputs with human preferences.
Updated 8 August 2026
Specifications
No specifications recorded yet.
Latest developments
Unsloth vs Axolotl vs TRL vs LLaMA-Factory: A Fine-Tuning Framework Comparison on Speed, VRAM, and Multi-GPU
MarkTechPost · 1 month ago ·
32
Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL
Hugging Face · 3 months ago ·
8
Make LLM Fine-tuning 2x faster with Unsloth and 🤗 TRL
Hugging Face · 2 years ago ·
24
Finetune Stable Diffusion Models with DDPO via TRL
Hugging Face · 2 years ago ·
54
July 2026
May 2026
January 2024
September 2023
Relationships
Products & technology
- Hugging Face develops this model · 2 sources
- Integrated with Stable Diffusion · 1 source
- Unsloth integrated with this model · 1 source