Instructions to use openai/clip-vit-large-patch14-336 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/clip-vit-large-patch14-336 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-large-patch14-336") 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("openai/clip-vit-large-patch14-336") model = AutoModelForZeroShotImageClassification.from_pretrained("openai/clip-vit-large-patch14-336") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d292ee69fba9d1360d4927a13347f3c89ba7381dec861a283ba0c383142214c
- Size of remote file:
- 1.71 GB
- SHA256:
- c6032c2e0caae3dc2d4fba35535fa6307dbb49df59c7e182b1bc4b3329b81801
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