Instructions to use dylanmontoya22/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dylanmontoya22/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dylanmontoya22/vit_model") 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("dylanmontoya22/vit_model") model = AutoModelForImageClassification.from_pretrained("dylanmontoya22/vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d1d7f4b9adc26f1f31184680e16befc7b9641d85a02585440be064f407f2d77
- Size of remote file:
- 4.6 kB
- SHA256:
- e1fc4480550f49a81884c955000fa53b9994623d7f17321a8a05136f67c46c4b
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