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Fine-tuning a Hugging Face model locally v1.0.0

Use this resource to fine-tune a Hugging Face model on a local GPU when no dedicated TAO skill fits

New

  • 343 downloads
  • 188 likes
  • 161 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install finetune-huggingface-models-locally

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent follows six steps: model inspection, hardware audit and NGC image, recipe research, project generation and smoke test, training, then publication to the Hub with a model card. It relies on live-fetched documentation with local references as fallback. You get a self-contained, reproducible training project.

Mostly picked by

Updated November 2, 2026

Card for the “Fine-tuning a Hugging Face model locally” skill

Details

Works in
Install guides
Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • references/detailed-workflow.md: detailed procedure
  • references/core-rules.md: core rules
  • references/dataset-sources.md: dataset sources

Good fit for

  • You want to fine-tune a Hugging Face model outside the dedicated TAO models
  • You want to publish a fine-tuned model with its card on the Hub

Not for

    Tags

    • Hugging Face
    • fine-tuning
    • LoRA
    • GPU

    About

    You say

    “Fine-tune this Hugging Face object detection model on my local dataset and publish it to the Hub.”

    Card for the “Fine-tuning a Hugging Face model locally” skill

    Skill published by nvidia under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to fine-tune a Hugging Face model on a local GPU when no dedicated TAO skill fits
    3. Review and adjust the result

    Content preview

    Files

    • BENCHMARK.md7.8 KB
    • config/skillspector-baseline.yaml4.5 KB
    • eval.config2.5 KB
    • evals/evals.json3.6 KB
    • LICENSE11.3 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • references/compat-workarounds.md12.1 KB
    • references/core-rules.md4.8 KB
    • references/cv-scripts.md34.1 KB
    • references/dataset-patterns.md10.9 KB
    • references/dataset-recommendations.md11.3 KB
    • references/dataset-sources.md17.8 KB
    • references/deliverables.md20.6 KB
    • references/detailed-workflow.md0.7 KB
    • references/docker-runs.md9.2 KB
    • references/error-playbook.md3.8 KB
    • references/hardware-container.md8.9 KB
    • references/hub-push.md5.6 KB
    • references/model-discovery.md10.8 KB
    • references/pipeline-skill-template.md9.2 KB
    • references/progress-tracking.md9.9 KB
    • references/reporting.md18.9 KB
    • references/research-priorities.md6.6 KB
    • references/testing.md21.4 KB
    • references/vlm-scripts.md28.5 KB
    • references/workflow-generate-train.md7.8 KB
    • references/workflow-intake-preflight.md23.4 KB
    • references/workflow-push-rerun.md3 KB
    • skill-card.md5 KB
    • SKILL.md19.6 KB
    • skill.oms.sig10.2 KB

    Origin and licence

    Listed unmodified

    Author
    nvidia
    Source
    github.com/nvidia/skills/tree/ca116d60beafe1b4459f0ab790b7b450912c56b0/skills/tao-finetune-huggingface-model
    Licence
    Apache-2.0

    Notice

    « tao-finetune-huggingface-model » (nvidia, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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