# open-clip-torch Connects images with text descriptions enabling search by words and automatic content filtering systems. **Details** - Model name: `open-clip-torch` - Model source: [https://github.com/mlfoundations/open_clip](https://github.com/mlfoundations/open_clip) - Model author: Gabriel Ilharco, et al. - Model license: MIT - Exposes embeddings? yes - Tags: `text-embeddings, classification, logits, embeddings, torch, clip, zero-shot, transformer` **Requirements** - Packages: `torch, torchvision, open_clip_torch` - 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("open-clip-torch") dataset.apply_model(model, label_field="predictions") session = fo.launch_app(dataset) # # Make zero-shot predictions with custom classes # model = foz.load_zoo_model( "open-clip-torch", text_prompt="A photo of a", classes=["person", "dog", "cat", "bird", "car", "tree", "chair"], ) dataset.apply_model(model, label_field="predictions") session.refresh() ```