huggingface-vision-trainer

Topics in the source

• Vision Model Training on Hugging Face Jobs
• When to Use This Skill
• Related Skills
• Local Script Execution
• Prerequisites Checklist
• Account & Authentication
• Dataset Requirements — Object Detection
• Dataset Requirements — Image Classification

Train object detection, image classification, and SAM/SAM2 segmentation models on managed cloud GPUs. No local GPU setup required—results are automatically saved to the Hugging Face Hub. Use this skill when users want to: Fine-tune object detection models (D-FINE, RT-DETR v2, DETR, YOLOS) on cloud GPUs or local Fine-tune image classification models (timm: MobileNetV3, MobileViT, ResNet, ViT/DINOv3, or any Transformers classifier) on cloud GPUs or local Fine-tune SAM or SAM2 models for segmentation / image matting using bbox or point prompts Train bounding-box detectors on custom datasets Train image classifiers on custom datasets Train segmentation models on custom mask datasets with prompts Run vision training jobs on Hugging Face Jobs infrastructure Ensure trained vision models are permanently saved to the Hub hugging-face-jobs — General HF Jobs infrastructure: token authentication, hardware flavors, timeout management, cost estimation, secrets, environment variables, scheduled jobs, and result persistence. Refer to the Jobs skill for any non-training-specific Jobs questions (e.g., "how do secrets work?", "what hardware is available?", "how do I pass tokens?"). hugging-face-model

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