Overview
What It Does
Tao Finetune Huggingface Model packages a focused communication workflow for an AI agent. Fine-tune any HuggingFace CV / VLM / LLM model on local NVIDIA GPUs inside an NGC PyTorch container. Use when the user wants to fine-tune a HuggingFace model (full or LoRA), train a vision / VLM / LLM model end-to-end, generate a reproducible HF training pipeline, smoke-test a HuggingFace model locally before scale-up, push a fine-tuned model to the HF Hub with a model card, or emit a self-contained rerun skill for an existing HuggingFace finetune. Supports image classification, object detection, semantic / instance / panoptic segmentation, depth estimation, image-text-to-text VLM (SFT / LoRA), and LLM SFT / DPO / GRPO. Six-step workflow: inspect and qualify, hardware and NGC image, research, generate and smoke, train + eval + infer, push and emit rerun skill. It is best suited to users who can review the resulting actions and provide only the accounts, files, or command access needed for the task. It is not a substitute for human approval on destructive, financial, security-sensitive, or public-facing actions.
Task ideas
Popular Use Cases
- Draft and organize messages
- Work with communication channels and contacts
- Summarize conversations into next steps
- Automate routine coordination
Installation
Install this Agent Skill
Claude Code
npx skills add https://github.com/NVIDIA/skills --skill tao-finetune-huggingface-modelCommands derived from the public GitHub SKILL.md record. Checked 2026-09-02. Review the source before running them.
Before you start
Requirements
| Claude Code | Required / review |
| Codex | Required / review |
| Public SKILL.md source | Required / review |
| Review instructions and requested permissions before installation | Required / review |
| Paid service | Check source |
| Supported system | Check source |
Popularity context
Why It’s Popular
Tao Finetune Huggingface Model is a verified Agent Skill from NVIDIA with a public SKILL.md, compatible with Claude Code, Codex.
Alternatives