Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use ManuD/vit_for_dfl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ManuD/vit_for_dfl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ManuD/vit_for_dfl") 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("ManuD/vit_for_dfl") model = AutoModelForImageClassification.from_pretrained("ManuD/vit_for_dfl") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Jan03_16-10-00_a04fae76209e/events.out.tfevents.1672762205.a04fae76209e.56959.2
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