Instructions to use samanehs/test_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use samanehs/test_bert with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://samanehs/test_bert") - Keras
How to use samanehs/test_bert with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://samanehs/test_bert") - Notebooks
- Google Colab
- Kaggle
| { | |
| "module": "keras_nlp.models.bert.bert_preprocessor", | |
| "class_name": "BertPreprocessor", | |
| "config": { | |
| "name": "bert_preprocessor", | |
| "trainable": true, | |
| "dtype": "float32", | |
| "tokenizer": { | |
| "module": "keras_nlp.models.bert.bert_tokenizer", | |
| "class_name": "BertTokenizer", | |
| "config": { | |
| "name": "bert_tokenizer", | |
| "trainable": true, | |
| "dtype": "int32", | |
| "vocabulary": null, | |
| "sequence_length": null, | |
| "lowercase": true, | |
| "strip_accents": false, | |
| "split": true, | |
| "suffix_indicator": "##", | |
| "oov_token": "[UNK]" | |
| }, | |
| "registered_name": "keras_nlp>BertTokenizer" | |
| }, | |
| "sequence_length": 512, | |
| "truncate": "round_robin" | |
| }, | |
| "registered_name": "keras_nlp>BertPreprocessor" | |
| } |