Hugging Face Model Trainer

by lidge-jun · devops · python, bash, docker, git, skill

Train/fine-tune LLMs using TRL on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO, reward modeling, GGUF conversion, dataset validation, hardware selection, cost estimation, Trackio monitoring, and model persistence. Invoke for cloud GPU training or GGUF conversion.

Source: https://github.com/lidge-jun/cli-jaw-skills

Install

git clone https://github.com/lidge-jun/cli-jaw-skills

Tags: python, bash, docker, git, skill

⭐ 4 GitHub stars · Source: skillsdirectory

About devops MCP servers and Claude skills

devops MCP servers extend what AI agents can do inside Claude Code, Cursor, Copilot, Codex, and Windsurf. The Skiln directory indexes 16,000+ such integrations across 22 categories.

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Frequently asked questions

How do I install Hugging Face Model Trainer?

Add the install command above to your Claude Code, Cursor, or Windsurf MCP configuration. Most servers register via npx, a local command, or a Docker image. Refer to the source repository for environment variables and credential requirements.

Which clients support Hugging Face Model Trainer?

Any MCP-compatible client works: Claude Desktop, Claude Code CLI, Cursor, Windsurf, Zed, and VS Code with the official MCP extension. OpenAI Codex and GitHub Copilot increasingly support MCP via adapter bridges.

Is Hugging Face Model Trainer free?

The server itself is typically open source. Any upstream service (API keys, paid tiers, hosted infrastructure) may have its own pricing. Check the source repository for details.