Instructions to use hf-internal-testing/tiny-random-SiglipForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-SiglipForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-SiglipForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-SiglipForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-SiglipForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39e9e04e2f1be910f265bbb9e71c8f06b1ffa1d2c0c2d1a63d2244340e57f86e
- Size of remote file:
- 118 kB
- SHA256:
- d5fae41928b33b7bfc70e768c8d116ed60e3887be9b9b27da19a79287b87a682
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