Instructions to use hf-internal-testing/tiny-random-vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-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("hf-internal-testing/tiny-random-vit") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-vit") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5c80c73a68eba974f6c210c68ae080942d9af0ed2dd824ae13681bfce27c4fc
- Size of remote file:
- 176 kB
- SHA256:
- b38d069d27638fcf45c8f98d40b83e49b0987b7bb4743f140c5bde91c78f10a3
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