Image Classification
Transformers
PyTorch
TensorBoard
deit
Generated from Trainer
Eval Results (legacy)
Instructions to use tcvrishank/histo_train_deit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tcvrishank/histo_train_deit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tcvrishank/histo_train_deit") 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("tcvrishank/histo_train_deit") model = AutoModelForImageClassification.from_pretrained("tcvrishank/histo_train_deit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a8f362ea8cae2b69574054f248754bbc8da98a19d2f593241bd76d2e704664f
- Size of remote file:
- 343 MB
- SHA256:
- 232eb9dc65044260e96ebb255ccdb1ce4c39655c8bf36700183f8f1008229768
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