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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78c9f9796ad1c8e66918e88fb0cf7567b3213a7cd3d672793b0eb4217453d419
- Size of remote file:
- 348 MB
- SHA256:
- 614ca0fa643da49450cfecff1a6f9cc31462c85dee10b423be1aeb558a42bc7f
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