Instructions to use hf-internal-testing/tiny-random-AlignModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AlignModel 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-AlignModel") 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-AlignModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-internal-testing/tiny-random-AlignModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 934f3b44e6526a1575f31ea406e82f66276b931437d38067c409a546c4579796
- Size of remote file:
- 3.11 MB
- SHA256:
- 96298c7b5fce2e1fb4d5e8048b65ff1f6e6c9877a2d50fd6f9cfadcb147c0aa2
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