Is huggingface-vision-trainer safe?
Grade A, 100/100. No meaningful risk found.
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.
Ahuggingface-vision-trainer
skills/huggingface-vision-trainer100/100 · No meaningful risk foundNo security findings
huggingface-vision-trainer
skills/huggingface-vision-trainerTrains 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.
- Content hash
- sha256:8ef38277b09da5bc768d984e8fb9447f28af65fc69b39ca37c08697d3e720a1f
- Files
- 12
- Quality
- 100/100
Security findings
None of the 30 rules matched.
Quality
- infoSKILL.md is longSL705 · skills/huggingface-vision-trainer/SKILL.md:1
594 linesLong skills spend context on every load. Fix: Keep SKILL.md under 500 lines and move reference material into linked files.
Files in this skill
- SKILL.md29.5 KB
- references/finetune_sam2_trainer.md6.3 KB
- references/hub_saving.md16.6 KB
- references/image_classification_training_notebook.md10.8 KB
- references/object_detection_training_notebook.md29.2 KB
- references/reliability_principles.md9.3 KB
- references/timm_trainer.md3.5 KB
- scripts/dataset_inspector.py31.1 KB
- scripts/estimate_cost.py7.2 KB
- scripts/image_classification_training.py13.1 KB
- scripts/object_detection_training.py26.7 KB
- scripts/sam_segmentation_training.py13.6 KB
Questions about huggingface-vision-trainer
- Is huggingface-vision-trainer safe to install?
- Our scanner gave huggingface-vision-trainer grade A (100/100): no meaningful risk found. None of the 30 security rules matched. Static analysis cannot prove safety, so pin the reviewed revision with a lockfile.
- How do I install huggingface-vision-trainer in Claude Code or Codex?
- Run skillhash add github:huggingface/skills/skills/huggingface-vision-trainer. It downloads the exact commit, checks the grade against your policy, writes skills.lock and installs it into .claude/skills and .agents/skills.
- What happens if huggingface-vision-trainer changes upstream?
- Its content hash changes. skillhash verify fails in CI until you review the new version and update the lock. With a watch, you also get an alert.
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