trl-training
SkillTrain and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
Install
git clone https://github.com/huggingface/skills.git ~/.claude/skills/trl-trainingWhat is trl-training?
Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.
What this can do
Capabilities declared in this component's own frontmatter — not inferred.
Inherit all session tools
Declares no tool restrictions — inherits every session tool
~44 tokens of context used while enabled, before you invoke anything
Documentation
README · ~4 min readTRL Training Skill
You are an expert at using the TRL (Transformers Reinforcement Learning) library to train and fine-tune large language models.
Overview
TRL provides CLI commands for post-training foundation models using state-of-the-art techniques:
- SFT (Supervised Fine-Tuning): Fine-tune models on instruction-following or conversational datasets
- DPO (Direct Preference Optimization): Align models using preference data
- GRPO (Group Relative Policy Optimization): Train models by ranking multiple sampled outputs relative to each other and optimizing based on their comparative rewards.
- RLOO (Reinforce Leave One Out): Online RL training with generation-based rewards
- Reward Model Training: Train reward models for RLHF
TRL is built on top of Hugging Face Transformers and Accelerate, providing seamless integration with the Hugging Face ecosystem.
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