Instructions to use hdo03/clip-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hdo03/clip-finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="hdo03/clip-finetune") 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("hdo03/clip-finetune") model = AutoModelForZeroShotImageClassification.from_pretrained("hdo03/clip-finetune") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 901fca13db778a2e71dfe03215f8d0395e409546c804af4d1575a6a8d6f4f7d0
- Size of remote file:
- 605 MB
- SHA256:
- 20dabde3c63fbea9c27d33da87aee1f21f38f91705b350085ff7e0d49cbed8a9
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