# monet-zero-torch CLIP‑based vision‑language model for zero‑shot dermatology image classification.. **Details** - Model name: `monet-zero-torch` - Model source: [https://huggingface.co/suinleelab/monet](https://huggingface.co/suinleelab/monet) - Model author: Su‑In Lee Lab - Model license: MIT - Model size: 1.59 GB - Exposes embeddings? yes - Tags: `text-embeddings, classification, torch, official, medical, embeddings` **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("monet-zero-torch") dataset.apply_model(model, label_field="predictions") session = fo.launch_app(dataset) ```