Instructions to use keras/flan_large_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/flan_large_multi with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/flan_large_multi") - Keras
How to use keras/flan_large_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/flan_large_multi") - Notebooks
- Google Colab
- Kaggle
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library_name: keras-hub
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##
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⚠️ T5 is currently only available via the `keras-hub-nightly` package. Use `pip install keras-hub-nightly` to try this model.
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T5 encoder-decoder backbone model.
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library_name: keras-hub
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## Model Overview
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⚠️ T5 is currently only available via the `keras-hub-nightly` package. Use `pip install keras-hub-nightly` to try this model.
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T5 encoder-decoder backbone model.
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