Instructions to use jayavardhan31/VIT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavardhan31/VIT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jayavardhan31/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("jayavardhan31/VIT") model = AutoModelForImageClassification.from_pretrained("jayavardhan31/VIT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 392c76086ec279a743e736609037d23afc0e6d30c90a40822cfa4f4a2a067f5d
- Size of remote file:
- 15.1 kB
- SHA256:
- 18164335bf9ef14d230cc3c47ba8a3c7f92caa920c1c77cd2588ab7ab350451c
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