Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification") 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("gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification") model = AutoModelForImageClassification.from_pretrained("gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/resolve/main/training_args.bin
- Command line
-
hf download hf://gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gianlab/swin-tiny-patch4-window7-224-finetuned-ecg-classification/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- dd36b37849e9d2c1ddb61d70b1de252752373faacd186d68999a45b5450e25c4
- Size of remote file:
- 4.66 kB
- SHA256:
- c0f6463619e11c124cb8f04660fe71335bbeb2cc5382fb077ce0a85355575516
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