Instructions to use hf-internal-testing/tiny-random-AltCLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AltCLIPModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="hf-internal-testing/tiny-random-AltCLIPModel") 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("hf-internal-testing/tiny-random-AltCLIPModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-internal-testing/tiny-random-AltCLIPModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0bb89b82a6c54e46dfbf74fb92883b9e9c53d55d1f48d6beaf060a8c6e5ad268
- Size of remote file:
- 548 kB
- SHA256:
- 9dc314e9d43fd92fa496b772ebd580f71ec7e1eed341f30cdfb8c9504dc90004
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