grpo-rl-training

What problem does it solve?

This Skill streamlines the process of fine-tuning large language models using Group Relative Policy Optimization (GRPO) with the TRL library, enabling custom behavior alignment and task-specific optimization.

Core Features & Use Cases

• GRPO Implementation: Provides a robust framework for GRPO training, focusing on reward function design and hyperparameter tuning.
• Customizable Rewards: Supports multiple, composable reward functions for enforcing format, correctness, and style.
• Use Case: Fine-tune a model to generate structured JSON outputs for API calls, ensuring both correct data formatting and accurate information retrieval.

Quick Start

Use the grpo-rl-training skill to fine-tune a model for math reasoning tasks.