部署与运维

huggingface-llm-trainer

Name: huggingface-llm-trainer
Author: huggingface

huggingface/skills

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, model selection/leaderboards and model persistence. Use for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

2271 次安装
1.1万星标
收录于 2026.03.23

安装命令

$ npx skills add https://github.com/huggingface/skills --skill huggingface-llm-trainer

SKILL.md

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.

SKILL.md

TRL Training on Hugging Face Jobs

Overview

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