Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ArturoGL/vit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArturoGL/vit-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ArturoGL/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("ArturoGL/vit-model") model = AutoModelForImageClassification.from_pretrained("ArturoGL/vit-model") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
runs/Sep13_20-19-41_3348018a0b56/events.out.tfevents.1694636405.3348018a0b56.363.0
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