Instructions to use Balajim57/zero-shot-vitb32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Balajim57/zero-shot-vitb32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="Balajim57/zero-shot-vitb32") 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("Balajim57/zero-shot-vitb32") model = AutoModelForZeroShotImageClassification.from_pretrained("Balajim57/zero-shot-vitb32") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- flax_model.msgpack +3 -0
- pytorch_model.bin +3 -0
- tf_model.h5 +3 -0
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