Instructions to use samanehs/bert_tiny_en_uncased_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use samanehs/bert_tiny_en_uncased_classifier with KerasHub:
import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://samanehs/bert_tiny_en_uncased_classifier") - Keras
How to use samanehs/bert_tiny_en_uncased_classifier 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/bert_tiny_en_uncased_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dbb58bae0b98e1058ddec8ba2a007bf6e20a557025a9571e733b8563f35200ea
- Size of remote file:
- 52.8 MB
- SHA256:
- ce3b160925e8ce4f87b80ee2f21968944d177f3be2b7c1066796a7ec82a3617a
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