Instructions to use ab2-gbl/ECG_segmentation_using_U-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ab2-gbl/ECG_segmentation_using_U-Net with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://ab2-gbl/ECG_segmentation_using_U-Net") - Notebooks
- Google Colab
- Kaggle
Download TCN.keras from ab2-gbl/ECG_segmentation_using_U-Net: direct link, hf CLI and curl.
- Browser
- Download file 3.85 MB
-
https://huggingface.co/ab2-gbl/ECG_segmentation_using_U-Net/resolve/main/TCN.keras
- Command line
-
hf download hf://ab2-gbl/ECG_segmentation_using_U-Net/TCN.keras
-
curl -L -o TCN.keras https://huggingface.co/ab2-gbl/ECG_segmentation_using_U-Net/resolve/main/TCN.keras
3.85 MB
- Xet hash:
- 2223661a57c3f1743a6796748375ee7e5591952736f5ef2968f3f5c34888ed9b
- Size of remote file:
- 3.85 MB
- SHA256:
- 6a6f33553ba132f095bd4b2656e075ed5f352a16a29b9448a690e35fac056749
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