Instructions to use Grey01/bart_billsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use Grey01/bart_billsum with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://Grey01/bart_billsum") - Keras
How to use Grey01/bart_billsum with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Grey01/bart_billsum") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_nlp.src.models.bart.bart_seq_2_seq_lm_preprocessor", | |
| "class_name": "BartSeq2SeqLMPreprocessor", | |
| "config": { | |
| "name": "bart_seq2_seq_lm_preprocessor", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "mixed_float16" | |
| }, | |
| "registered_name": null | |
| }, | |
| "tokenizer": { | |
| "module": "keras_nlp.src.models.bart.bart_tokenizer", | |
| "class_name": "BartTokenizer", | |
| "config": { | |
| "name": "bart_tokenizer", | |
| "trainable": true, | |
| "dtype": { | |
| "module": "keras", | |
| "class_name": "DTypePolicy", | |
| "config": { | |
| "name": "int32" | |
| }, | |
| "registered_name": null | |
| }, | |
| "sequence_length": null, | |
| "add_prefix_space": false | |
| }, | |
| "registered_name": "keras_nlp>BartTokenizer" | |
| }, | |
| "encoder_sequence_length": 512, | |
| "decoder_sequence_length": 128 | |
| }, | |
| "registered_name": "keras_nlp>BartSeq2SeqLMPreprocessor" | |
| } |