Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use 02shanky/test_model_graphics_classification_LION with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 02shanky/test_model_graphics_classification_LION with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="02shanky/test_model_graphics_classification_LION") 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("02shanky/test_model_graphics_classification_LION") model = AutoModelForImageClassification.from_pretrained("02shanky/test_model_graphics_classification_LION") - Notebooks
- Google Colab
- Kaggle
Fully Trained Model with LION optimizer
Browse files
runs/Jul12_08-51-00_cf3a6ec8eae5/events.out.tfevents.1689151866.cf3a6ec8eae5.2996.0
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