Instructions to use ydshieh/tiny-random-ViTForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-ViTForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ydshieh/tiny-random-ViTForImageClassification") 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("ydshieh/tiny-random-ViTForImageClassification") model = AutoModelForImageClassification.from_pretrained("ydshieh/tiny-random-ViTForImageClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea9e95396355e44be40bcd298f58c1706affa4003bc665890636b0cbda011a4d
- Size of remote file:
- 176 kB
- SHA256:
- 09f684bbcb2a68fc16285212377f766fbb7f287ba443cbd674dd70f20d6ca91c
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