Instructions to use optimum-intel-internal-testing/tiny-random-vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use optimum-intel-internal-testing/tiny-random-vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="optimum-intel-internal-testing/tiny-random-vit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("optimum-intel-internal-testing/tiny-random-vit") model = AutoModelForImageClassification.from_pretrained("optimum-intel-internal-testing/tiny-random-vit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 201098390ef20ebd30f54aac18d2b3dcaab9028cb47fcf2dedb507e64ade151d
- Size of remote file:
- 199 kB
- SHA256:
- c24aefb91f22827cd1192ee92438e6ddcd2f32284b71d370834fa3119551f739
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