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Real file from a public repo · synced Sep 3, 2026

huggingface-vision-trainer

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.

huggingface/skills1.5k installsApache-2.0

Works with

Claude CodeCursorCodex CLIGitHub CopilotGemini CLI

Install in three steps

  1. 1

    Download the ZIP

    One file per agent, plus INSTALL.md with the exact paths below.

  2. 2

    Claude Code: copy SKILL.md into your skills folder

    .claude/skills/huggingface-vision-trainer/SKILL.md    # this project
    ~/.claude/skills/huggingface-vision-trainer/SKILL.md   # every project
  3. 3

    Other agents: use the matching file

    skill.mdc goes in Cursor’s .cursor/rules/. AGENTS.md works as GitHub Copilot instructions, a legacy .cursorrules, or a Codex / Gemini CLI instructions file.

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