skills.vishalvoidskills/vishalvoid
Technical & DevelopmentIntermediate

hugging-face-model-trainer

Train models with TRL: SFT, DPO, GRPO, GGUF conversion

Developer Setup

Setup & Installation

bash
npx skills add https://github.com/huggingface/skills --skill hugging-face-model-trainer

Overview

What This Skill Does

Trains and fine-tunes language models on Hugging Face's cloud GPU infrastructure using TRL. Supports SFT, DPO, GRPO, and reward modeling. Handles job submission, dataset validation, cost estimation, and GGUF conversion for local deployment.

Application

When to use this Skill

Documentation

Show Skills.md file

TRL Training on Hugging Face Jobs

Overview

Train language models using TRL (Transformer Reinforcement Learning) on fully managed Hugging Face infrastructure. No local GPU setup required—models train on cloud GPUs and results are automatically saved to the Hugging Face Hub.

TRL provides multiple training methods:

  • SFT (Supervised Fine-Tuning) - Standard instruction tuning
  • DPO (Direct Preference Optimization) - Alignment from preference data
  • GRPO (Group Relative Policy Optimization) - Online RL training
  • Reward Modeling - Train reward models for RLHF

For detailed TRL method documentation:

hf_doc_search("your query", product="trl")
hf_doc_fetch("https://huggingface.co/docs/trl/sft_trainer")  # SFT
hf_doc_fetch("https://huggingface.co/docs/trl/dpo_trainer")  # DPO
# etc.

See also: references/training_methods.md for method overviews and selection guidance

When to Use This Skill

Use this skill when users want to:

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