Instructions to use kavorite/e6clip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kavorite/e6clip with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="kavorite/e6clip") 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("kavorite/e6clip") model = AutoModelForZeroShotImageClassification.from_pretrained("kavorite/e6clip") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1a475e2260a288e8571467ba7417d07c42f3a17a0fb97bb5a6ef1af79342c1b
- Size of remote file:
- 303 MB
- SHA256:
- 88eaad2f38ee285bc6387727c490512fe7fb05f8bb0e41681c55ae41679ce741
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