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
- Xet hash:
- 079d2bc7aa32f2e6617797d662af2444af0cb54f9dd9b73012c029638ae6687c
- Size of remote file:
- 343 MB
- SHA256:
- 58c6e56db375e02e6422b9e13574f7aedd7a989e667c8491276f576c8a5e5a38
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