Image Classification
Transformers
PyTorch
TensorBoard
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use mshuggingface/swin-tiny-patch4-window7-224-ms-test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mshuggingface/swin-tiny-patch4-window7-224-ms-test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mshuggingface/swin-tiny-patch4-window7-224-ms-test1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("mshuggingface/swin-tiny-patch4-window7-224-ms-test1") model = AutoModelForImageClassification.from_pretrained("mshuggingface/swin-tiny-patch4-window7-224-ms-test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mshuggingface/swin-tiny-patch4-window7-224-ms-test1: direct link, hf CLI and curl.
- Browser
- Download file 3.44 kB
-
https://huggingface.co/mshuggingface/swin-tiny-patch4-window7-224-ms-test1/resolve/main/training_args.bin
- Command line
-
hf download hf://mshuggingface/swin-tiny-patch4-window7-224-ms-test1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mshuggingface/swin-tiny-patch4-window7-224-ms-test1/resolve/main/training_args.bin
3.44 kB
- Xet hash:
- fc4b512515ec672cb3fd4ec4ca4d66af09c98552e0e19a93408eff66ef117237
- Size of remote file:
- 3.44 kB
- SHA256:
- e5031ef433c3609167f5d05f9510e71aab3733043dc4924b5e1dfb14aaa89ed1
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