Instructions to use hf-tiny-model-private/tiny-random-AlignModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/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-tiny-model-private/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-tiny-model-private/tiny-random-AlignModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-AlignModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 244d229a1c0082588dee7092be706242d5fa0c4794b5574ecf290f4b54db849a
- Size of remote file:
- 3.11 MB
- SHA256:
- 8c8db4db4fc28485fa92b5559e2da50c8e761f5b9c3ead417d2359124e356f5d
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