Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use amjadfqs/finalProject with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amjadfqs/finalProject with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amjadfqs/finalProject") 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("amjadfqs/finalProject") model = AutoModelForImageClassification.from_pretrained("amjadfqs/finalProject") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e275386f9046eb50885ceae1e3b03ea9bb58c2c975a562c778b1ba87d4a1ce6e
- Size of remote file:
- 3.9 kB
- SHA256:
- 34c14a944fba9678a2a15c09651d86b54f0a107fcc52b4a20f928a602e7d11f2
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