Instructions to use keras/whisper_base_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/whisper_base_multi with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/whisper_base_multi") - Keras
How to use keras/whisper_base_multi with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://keras/whisper_base_multi") - Notebooks
- Google Colab
- Kaggle
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README.md
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third party and subject to a separate license, available
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[here](https://github.com/openai/whisper).
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__Arguments__
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third party and subject to a separate license, available
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[here](https://github.com/openai/whisper).
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## Links
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* [Whisper Quickstart Notebook](coming soon)
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* [Whisper API Documentation](https://keras.io/keras_hub/api/models/whisper/)
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* [KerasHub Beginner Guide](https://keras.io/guides/keras_hub/getting_started/)
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* [KerasHub Model Publishing Guide](https://keras.io/guides/keras_hub/upload/)
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## Installation
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Keras and KerasHub can be installed with:
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```
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pip install -U -q keras-hub
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pip install -U -q keras
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```
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Jax, TensorFlow, and Torch come preinstalled in Kaggle Notebooks. For instructions on installing them in another environment see the [Keras Getting Started](https://keras.io/getting_started/) page.
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__Arguments__
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