Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
---
name: grpo-rl-training
description: Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Post-Training, Reinforcement Learning, GRPO, TRL, RLHF, Reward Modeling, Reasoning, DPO, PPO, Structured Output]
dependencies: [transformers>=4.47.0, trl>=0.14.0, datasets>=3.2.0, peft>=0.14.0, torch]
---
# GRPO/RL Training with TRL
Expert-level guidance for implementing Group Relative Policy Optimization (GRPO) using the Transformer Reinforcement Learning (TRL) library. This skill provides battle-tested patterns, critical insights, and production-ready workflows for fine-tuning language models with custom reward functions.
## When to Use This Skill
Use GRPO training when you need to:
- **Enforce specific output formats** (e.g., XML tags, JSON, structured reasoning)
- **Teach verifiable tasks** with objective correctness metrics (math, coding, fact-checking)
- **Improve reasoning capabilities** by rewarding chain-of-thought patterns
- **Align models to domain-specific behaviors** without labeled preference data
- **Optimize for multiple objectives** simultaneously (format + correctness + style)
**Do NOT use GRPO for:**
- Simple supervised fine-tuning tasks (use SFT instead)… load the full skill through Skill Me