Instructions to use facebook/metaclip-b16-fullcc2.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/metaclip-b16-fullcc2.5b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="facebook/metaclip-b16-fullcc2.5b") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("facebook/metaclip-b16-fullcc2.5b") model = AutoModelForZeroShotImageClassification.from_pretrained("facebook/metaclip-b16-fullcc2.5b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 916c45e3db336b7770b618d25c9fff98faf3a59a36b84e3f3ef7be23eeff4ab1
- Size of remote file:
- 599 MB
- SHA256:
- e029fba2b2f92c9f550f7e84e620e690fa4bdfadfd9e28819a5dd8cf1b3b614e
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