# group-vit-segmentation-transformer-torch Hugging Face Transformers model for zero-shot semantic segmentation. **Details** - Model name: `group-vit-segmentation-transformer-torch` - Model source: [https://huggingface.co/docs/transformers/en/tasks/mask_generation](https://huggingface.co/docs/transformers/en/tasks/mask_generation) - Model author: Thomas Wolf, et al. - Model license: Apache 2.0 - Model size: 212.80 MB - Exposes embeddings? yes - Tags: `text-embeddings, segmentation, embeddings, torch, transformers, zero-shot, official` **Requirements** - Packages: `torch, torchvision, transformers` - CPU support - yes - GPU support - yes **Example usage** ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset( "coco-2017", split="validation", dataset_name=fo.get_default_dataset_name(), max_samples=50, shuffle=True, ) model = foz.load_zoo_model("group-vit-segmentation-transformer-torch", text_prompt="A photo of a", classes=["person", "dog", "cat", "bird", "car", "tree", "other"]) dataset.apply_model(model, label_field="predictions") session = fo.launch_app(dataset) ```