Instructions to use keras/t5_1.1_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/t5_1.1_small with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/t5_1.1_small") - Keras
How to use keras/t5_1.1_small 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_1.1_small") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_hub.src.models.t5.t5_backbone", | |
| "class_name": "T5Backbone", | |
| "config": { | |
| "name": "t5_backbone", | |
| "trainable": true, | |
| "vocabulary_size": 32128, | |
| "hidden_dim": 512, | |
| "intermediate_dim": 1024, | |
| "num_layers": 8, | |
| "num_heads": 6, | |
| "activation": "gelu", | |
| "key_value_dim": 64, | |
| "dropout": 0.1, | |
| "use_gated_activation": true, | |
| "layer_norm_epsilon": 1e-06, | |
| "tie_embedding_weights": false | |
| }, | |
| "registered_name": "keras_hub>T5Backbone" | |
| } |