Instructions to use niobures/YAMNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use niobures/YAMNet 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://niobures/YAMNet") - Notebooks
- Google Colab
- Kaggle
Download YamNet (qualcomm)/YamNet_float.dlc from niobures/YAMNet: direct link, hf CLI and curl.
- Browser
- Download file 15 MB
-
https://huggingface.co/niobures/YAMNet/resolve/main/YamNet%20(qualcomm)/YamNet_float.dlc
- Command line
-
hf download 'hf://niobures/YAMNet/YamNet (qualcomm)/YamNet_float.dlc'
-
curl -L -o YamNet_float.dlc 'https://huggingface.co/niobures/YAMNet/resolve/main/YamNet%20(qualcomm)/YamNet_float.dlc'
15 MB
- Xet hash:
- 777d39bbd35d0efd5fa34f4b1da5f9e4b2342362bbc46cdd6eda998ed0af4459
- Size of remote file:
- 15 MB
- SHA256:
- cb31461e9ec4a54bd0b03a4c4a7efe842dd3f34f5557c1da8ee353f6b0e3c937
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