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.
Profile →npx skills add waybarrios/opencode-power-pack --skill trl-training --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# TRL 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. ## Core Commands ### trl sft - Supervised Fine-Tuning Fine-tune language models on instruction-following or conversational datasets. **Full training:** ```bash trl sft \ --model_name_or_path Qwen/Qwen2-0.5B \ --dataset_name trl-lib/Capybara \ --learning_rate 2.0e-5 \ --num_train_epochs 1 \ --packing \ --per_devi
- Overview
- Core Commands
- trl sft - Supervised Fine-Tuning
- trl dpo - Direct Preference Optimization
- trl grpo - Group Relative Policy Optimization
- trl rloo - Reinforce Leave One Out
- trl reward - Reward Model Training
- Configuration Files
- Distributed Training
- Troubleshooting
- CUDA Out of Memory
- Dataset Loading Issues
- Model Loading Issues
- Slow Training
trl sft \ trl dpo \ trl grpo \ trl rloo \ trl reward \ trl sft --config sft_config.yaml trl sft --config sft_config.yaml --learning_rate 1.0e-5 Generate custom config accelerate config Use custom config
What does the trl-training skill do?
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.
How do I install it?
Run `npx skills add waybarrios/opencode-power-pack --skill trl-training --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From waybarrios/opencode-power-pack, a repository with 443 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.