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:
- b5e510c9df281e068b941a90c6d74ffb84ab691a55e6009977120ab8cbe0c5cb
- Size of remote file:
- 3.58 kB
- SHA256:
- cc1c40a66dfab1f0e9a6965a7dd1e077b46e4d1fb1a3628727c15ff8e1ee98f7
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