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:
- cce945bd4d8ffc8f843f8fa43afd1b7157d57b428e668eca43739df76e2acc37
- Size of remote file:
- 3.03 MB
- SHA256:
- 588ec329005027c4e547b118ca7713948158439fa69d4bd37df06930cb09dc26
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