Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use pthpth/ViTFineTuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pthpth/ViTFineTuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pthpth/ViTFineTuned") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("pthpth/ViTFineTuned") model = AutoModelForImageClassification.from_pretrained("pthpth/ViTFineTuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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File used to fine tune the transformer. Used on google colab.
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Update README.md
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Update README.md
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update model card README.md
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End of training
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update model card README.md
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Model save
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Training in progress, epoch 0
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initial commit
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