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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc5bc6d545be4d8628d39e3c10df0ac0e913243ffcd1f35c0cb1a07fc9ef40a0
- Size of remote file:
- 4.8 kB
- SHA256:
- 20f78b2c36d3971eb56910289308001e4291726093ea9c35dab1dc4f333f8432
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