Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use alexrods/vit_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alexrods/vit_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="alexrods/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("alexrods/vit_model") model = AutoModelForImageClassification.from_pretrained("alexrods/vit_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 341b01ab1ee6531aca8fadda5263f7a00a4dcb540107ce9d010e2540da93fc23
- Size of remote file:
- 343 MB
- SHA256:
- 0176a6f4bf40cb3a1c94c2d3a33f9b976f28e7da1f75417bb40b1b565c21f84e
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