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 sb_vs_else_model.pkl from ab2-gbl/ECG_segmentation_using_U-Net: direct link, hf CLI and curl.
- Browser
- Download file 24.2 MB
-
https://huggingface.co/ab2-gbl/ECG_segmentation_using_U-Net/resolve/main/sb_vs_else_model.pkl
- Command line
-
hf download hf://ab2-gbl/ECG_segmentation_using_U-Net/sb_vs_else_model.pkl
-
curl -L -o sb_vs_else_model.pkl https://huggingface.co/ab2-gbl/ECG_segmentation_using_U-Net/resolve/main/sb_vs_else_model.pkl
24.2 MB
- Xet hash:
- 7acffb7f66dc9ec6942079091ae3d5ced6113aaf8fdf35ada1d2270c4ca8fb2e
- Size of remote file:
- 24.2 MB
- SHA256:
- d8f400fb4ae4b54ade3d509be44363a009cf5ee992b2f7edfeacacb318f62313
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