Instructions to use lewtun/tiny-clip-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lewtun/tiny-clip-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="lewtun/tiny-clip-test") 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("lewtun/tiny-clip-test") model = AutoModelForZeroShotImageClassification.from_pretrained("lewtun/tiny-clip-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6a2b4a4ebb839eeaf4c85f567cb3316a93ae8af8b76dec4e6a4072036950f4b
- Size of remote file:
- 6.71 MB
- SHA256:
- 2cd430b5485c1609f4502b8d803019acd6a2d849cf838b86a6583281a0f5d7bb
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