Instructions to use lechasseurgris/Tsinghua-BDMI_Spectrogram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use lechasseurgris/Tsinghua-BDMI_Spectrogram with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://lechasseurgris/Tsinghua-BDMI_Spectrogram") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff94d9e45056d715bbe74f9fe740abd16856cd1f181108796fd443757b4fb5f6
- Size of remote file:
- 117 MB
- SHA256:
- 9a5a4c45202601df58995ab9c7b2ab641919d17e01f6643f25da3589b2e14953
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