Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use djbp/swin-base-patch4-window7-224-MM_Classification_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbp/swin-base-patch4-window7-224-MM_Classification_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djbp/swin-base-patch4-window7-224-MM_Classification_base") 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("djbp/swin-base-patch4-window7-224-MM_Classification_base") model = AutoModelForImageClassification.from_pretrained("djbp/swin-base-patch4-window7-224-MM_Classification_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aca364acfaa96d1c52676bf9b0f59a383b40ae460e1e5e54a9438ace2ce418c0
- Size of remote file:
- 348 MB
- SHA256:
- d85e674dc68228e67515b026e7c08821158e09b56e66e777fbc5ab0fc69f70f9
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