Update README.md with new model card content
Browse files
README.md
CHANGED
|
@@ -5,7 +5,7 @@ tags:
|
|
| 5 |
- text-classification
|
| 6 |
pipeline_tag: text-classification
|
| 7 |
---
|
| 8 |
-
## Model Overview
|
| 9 |
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.
|
| 10 |
|
| 11 |
Weights and Keras model code are released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
|
|
@@ -144,4 +144,4 @@ classifier = keras_hub.models.BertClassifier.from_preset(
|
|
| 144 |
preprocessor=None,
|
| 145 |
)
|
| 146 |
classifier.fit(x=features, y=labels, batch_size=2)
|
| 147 |
-
```
|
|
|
|
| 5 |
- text-classification
|
| 6 |
pipeline_tag: text-classification
|
| 7 |
---
|
| 8 |
+
### Model Overview
|
| 9 |
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.
|
| 10 |
|
| 11 |
Weights and Keras model code are released under the [Apache 2 License](https://github.com/keras-team/keras-hub/blob/master/LICENSE).
|
|
|
|
| 144 |
preprocessor=None,
|
| 145 |
)
|
| 146 |
classifier.fit(x=features, y=labels, batch_size=2)
|
| 147 |
+
```
|