Instructions to use UsefulSensors/moonshine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use UsefulSensors/moonshine with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://UsefulSensors/moonshine") - Notebooks
- Google Colab
- Kaggle
Would you consider using KerasHub API's for this model?
#3
by Divyasreepat - opened
Sounds like a game changer for speech recognition!
Would you consider using KerasHub API's for this model?
- you could take advantage of the
save_to_preset()andfrom_preset()methods to load model presets from HuggingFace or Kaggle - you can easily upload to HuggingFace or Kaggle using
upload_preset()
Example of a KerasHub model on HF here - https://huggingface.co/google/paligemma-3b-pt-224-keras
Yes, absolutely. The inference code is already written in Keras 3. I haven't investigated keras-hub in detail, but will do so soon.
Great! Here are all of KerasHub models - https://huggingface.co/keras
Here is the GitHub repo for reference model implementations - https://github.com/keras-team/keras-hub/tree/master
This has been added to KerasHub - https://www.kaggle.com/models/keras/moonshine, https://github.com/keras-team/keras-hub/tree/master/keras_hub/src/models/moonshine