Instructions to use zeromodels/moonshine_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/moonshine_base with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/moonshine_base with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/moonshine_base") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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pipeline_tag: automatic-speech-recognition
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license: mit
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library_name: kerasformers
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tags:
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---
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pipeline_tag: automatic-speech-recognition
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license: mit
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library_name: kerasformers
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tags:
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- keras
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- kerasformers
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- moonshine
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- tensorflow
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- jax
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- pytorch
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---
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# moonshine_base (Keras 3)
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Pure-Keras 3 weights for [kerasformers](https://github.com/IMvision12/KerasFormers), mirrored from the GitHub release. License: `mit`.
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```python
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from kerasformers.models.moonshine import MoonshineSpeechToText, MoonshineProcessor
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model = MoonshineSpeechToText.from_weights("moonshine_base")
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processor = MoonshineProcessor.from_weights("moonshine_base")
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```
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