Instructions to use BrendaTellez/SoundClassificationCNNRNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use BrendaTellez/SoundClassificationCNNRNN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://BrendaTellez/SoundClassificationCNNRNN") - Notebooks
- Google Colab
- Kaggle
| license: openrail | |
| datasets: | |
| - ashraq/esc50 | |
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| library_name: keras | |
| pipeline_tag: audio-classification | |
| tags: | |
| - biology | |
| - code | |