TRL
Company huggingface.co ● Covered in 4 stories + Follow ✴ AI Graph
TRL (Transformers Reinforcement Learning) is a library developed by Hugging Face that provides tools for training transformer language models using methods including Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), Direct Preference Optimization (DPO), and Reward Modeling. The library is integrated with Hugging Face's transformers framework and offers multiple trainer implementations organized by method type, including online methods, reward modeling, offline methods, and knowledge distillation approaches. TRL supports integration with tools like vLLM and includes features for multi-environment agentic reinforcement learning and model optimization.
Updated 6 August 2026
Public sources: Official website
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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 ·
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TRL v1.0: Post-Training Library Built to Move with the Field
Hugging Face · 5 months ago ·
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No GPU left behind: Unlocking Efficiency with Co-located vLLM in TRL
Hugging Face · 1 year ago ·
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Vision Language Models Explained
Hugging Face · 2 years ago ·
30