Computer vision

Universal Image Segmentation with Mask2Former and OneFormer

Zero-shot image segmentation with CLIPSeg

Image Classification with AutoTrain

Fine-Tune a Semantic Segmentation Model with a Custom Dataset

Fine-Tune ViT for Image Classification with 🤗 Transformers

Image GPT

We find that, just as a large transformer model trained on language can generate coherent text, the same exact model trained on pixel sequences can generate coherent image completions and samples. By establishing a correlation between sample quality and image classification accuracy, we show that our best generative model also contains features competitive with top convolutional nets in the unsupervised setting.