hugging-face-vision-trainer
OfficialTrain vision models on Hugging Face Jobs
Software Engineering#object-detection#image-classification#huggingface-jobs#dataset-preparation#vision-training#sam-segmentation#hub-persistence
AuthorBlackRoad-OS-Inc
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Trains and fine-tunes object detection, image classification, and SAM/SAM2 vision models on Hugging Face Jobs cloud GPUs, removing the need for local GPU setup and enabling scalable experimentation.
Core Features & Use Cases
- Supports object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm-based models, ViT, ResNet), and SAM/SAM2 segmentation with prompt-based fine-tuning.
- Provides COCO-format dataset preparation, Albumentations-based augmentation, evaluation metrics (mAP, mAR), and Hub persistence with Trackio monitoring.
- Includes ready-to-run training scripts, dataset validation utilities, and cost estimation to help plan hardware and budgets.
Quick Start
Run a full training job on Hugging Face Jobs for vision models by selecting a model and dataset, then push the trained model to the Hub.
Dependency Matrix
Required Modules
transformers>=5.2.0accelerate>=1.1.0albumentations>=1.4.16timmdatasets>=4.0torchmetricspycocotoolstrackiohuggingface_hubmonaitorchvisionevaluatescikit-learn
Components
scriptsreferences
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Please help me install this Skill: Name: hugging-face-vision-trainer Download link: https://github.com/BlackRoad-OS-Inc/blackroad-operator/archive/main.zip#hugging-face-vision-trainer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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