huggingface/hugging-face-model-trainer
FreeTrain models with TRL: SFT, DPO, GRPO
FreeFree tier
About huggingface/hugging-face-model-trainer
The Hugging Face Model Trainer is an agent skill designed for training Hugging Face models using the Transformer Reinforcement Learning (TRL) library. It supports three major training methods: Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO), and Generative Reinforcement Policy Optimization (GRPO). This tool enables users to fine-tune language models with reinforcement learning techniques, making it suitable for customizing models for specific tasks or improving alignment with human preferences. It is part of the awesome-agent-skills collection and is open source.
Key Features
Supports Supervised Fine-Tuning (SFT)
Supports Direct Preference Optimization (DPO)
Supports Generative Reinforcement Policy Optimization (GRPO)
Built on the TRL library for reinforcement learning with transformers
Open-source agent skill for integration into workflows
Pros & Cons
Pros
- Supports multiple state-of-the-art training methods in one tool
- Open source and free to use
- Integrates with the Hugging Face ecosystem
Best For
Fine-tuning language models for specific tasks using supervised learningAligning model outputs with human preferences via DPOOptimizing model policies through generative reinforcement learning (GRPO)