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This entry duplicates huggingface-vision-trainer, which is the one we list in search.

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…

Skill by sediman-agent

IndexedNOASSERTION★ 394
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Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/sediman-agent-huggingface-vision-trainer

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

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.

Use cases: ml

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What's inside

Skill name
huggingface-vision-trainer
Description
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.
License
NOASSERTION
Instructions
590 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Agent Skills spec issues

  • body: 590 lines (spec recommends under 500)

Files (12)

  • SKILL.md
  • finetune_sam2_trainer.md · references/
  • hub_saving.md · references/
  • image_classification_training_notebook.md · references/
  • object_detection_training_notebook.md · references/
  • reliability_principles.md · references/
  • timm_trainer.md · references/
  • dataset_inspector.py · scripts/
  • estimate_cost.py · scripts/
  • image_classification_training.py · scripts/
  • object_detection_training.py · scripts/
  • sam_segmentation_training.py · scripts/

The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub

More from sediman-agent/OpenSkynet

Signals

Stars
394
Forks
44
Open issues
135
Last commit (this folder)
May 30, 2026 (5 months ago)
Last release
Jun 4, 2026 (4 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
NOASSERTION
Repository
github.com/sediman-agent/OpenSkynet
Website
agent.sediman.com/
First seen
Oct 24, 2026
Last checked
Oct 24, 2026
Source
GitHubgithub-graphql

Same skill elsewhere

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Cite this page

huggingface-vision-trainer skill. Agent Mart. https://agentmart.dev/skills/sediman-agent-huggingface-vision-trainer (last updated 2026-10-24)