Instructions to use keras/t5_large_multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/t5_large_multi with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/t5_large_multi") - Keras
How to use keras/t5_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/t5_large_multi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c93ca8738f7f730459106d851e6977a9de0c4879be85cc3991535eae0d998247
- Size of remote file:
- 2.95 GB
- SHA256:
- e143798343c312084853e2e24b62b3e38d3f421f5162973f70ff1f811f6c8010
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