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Update README.md with new model card content

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@@ -6,7 +6,7 @@ language:
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  tags:
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  - text-classification
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  ---
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- ## Model Overview
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  BERT (Bidirectional Encoder Representations from Transformers) is a set of language models published by Google. They are intended for classification and embedding of text, not for text-generation. See the model card below for benchmarks, data sources, and intended use cases.
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  Weights and Keras model code are released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
@@ -145,4 +145,4 @@ classifier = keras_hub.models.BertClassifier.from_preset(
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  preprocessor=None,
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  )
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  classifier.fit(x=features, y=labels, batch_size=2)
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- ```
 
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  tags:
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  - text-classification
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  ---
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+ ### Model Overview
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  BERT (Bidirectional Encoder Representations from Transformers) is a set of language models published by Google. They are intended for classification and embedding of text, not for text-generation. See the model card below for benchmarks, data sources, and intended use cases.
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  Weights and Keras model code are released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
 
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  preprocessor=None,
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  )
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  classifier.fit(x=features, y=labels, batch_size=2)
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+ ```