Instructions to use ChrisGoringe/vitH16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChrisGoringe/vitH16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="ChrisGoringe/vitH16") 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("ChrisGoringe/vitH16") model = AutoModelForZeroShotImageClassification.from_pretrained("ChrisGoringe/vitH16") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb05ac2f6a3a184a09da58fc01ea76bb64d5216ccb8f1de2dd934853dd1d372c
- Size of remote file:
- 1.97 GB
- SHA256:
- 42f2741cf7219d5557b63ac10e32935835574fae568698ae9a53e0110767d4fa
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