Instructions to use keras/whisper_tiny_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/whisper_tiny_multi with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/whisper_tiny_multi") - Keras
How to use keras/whisper_tiny_multi 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://keras/whisper_tiny_multi") - Notebooks
- Google Colab
- Kaggle
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README.md
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library_name: keras-hub
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##
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⚠️ Whisper is currently only available via the `keras-hub-nightly` package. Use `pip install keras-hub-nightly` to try this model.
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A Whisper encoder-decoder network for speech.
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- __max_decoder_sequence_length__: int. The maximum sequence length that the
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text decoder can consume.
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##
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```python
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import keras_hub
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import keras_core as keras
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library_name: keras-hub
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## Model Overview
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⚠️ Whisper is currently only available via the `keras-hub-nightly` package. Use `pip install keras-hub-nightly` to try this model.
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A Whisper encoder-decoder network for speech.
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- __max_decoder_sequence_length__: int. The maximum sequence length that the
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text decoder can consume.
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## Example Usage
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```python
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import keras_hub
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import keras_core as keras
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