Instructions to use hf-internal-testing/tiny-random-AltCLIPModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-AltCLIPModel 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-AltCLIPModel") 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-AltCLIPModel") model = AutoModelForZeroShotImageClassification.from_pretrained("hf-internal-testing/tiny-random-AltCLIPModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 380723b083bcce942f01c3214b9582d037938857908992a1120ffefe8c6bcc18
- Size of remote file:
- 586 kB
- SHA256:
- a2e2b1362e20fdbbc3534c828525a3285389513cf6c28a9b38926798c817fefb
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