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.tflite from niobures/YAMNet: direct link, hf CLI and curl.
- Browser
- Download file 14.9 MB
-
https://huggingface.co/niobures/YAMNet/resolve/main/YamNet%20(qualcomm)/YamNet_float.tflite
- Command line
-
hf download 'hf://niobures/YAMNet/YamNet (qualcomm)/YamNet_float.tflite'
-
curl -L -o YamNet_float.tflite 'https://huggingface.co/niobures/YAMNet/resolve/main/YamNet%20(qualcomm)/YamNet_float.tflite'
14.9 MB
- Xet hash:
- 9534850e757a2f0241a256d6aaa9e985f987cf089c6d2846cb1629f3c73f4122
- Size of remote file:
- 14.9 MB
- SHA256:
- d338ea0c32dceea6f8e1f1cd3dd4e0f99e34f250acc09bdfad4e37070d2f8775
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