Instructions to use hellothisisaswin/ecg-ptbxl-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hellothisisaswin/ecg-ptbxl-classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://hellothisisaswin/ecg-ptbxl-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 34c945ed41ba7d3bc7ea8f89204f946fb9658844ade65f9da8cf26255fbed88e
- Size of remote file:
- 8.43 MB
- SHA256:
- 3f2cdde86cb8fd2627f663ee620ebcc98e2d4f5470a70d07e6127ca3d480e51d
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