Instructions to use arampacha/clip-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/clip-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="arampacha/clip-test") 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("arampacha/clip-test") model = AutoModelForZeroShotImageClassification.from_pretrained("arampacha/clip-test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a13eb7b5973f9bf7f3ec1ceefcefd9e7874a73db223811adb3cac3780f43ba0
- Size of remote file:
- 605 MB
- SHA256:
- 2818acd403f288c90729ebd406c93485d5c7f789e457885fb5df9fb7502a6e3d
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