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tensorflow/lite/g3doc/examples/bert_qa/overview.md

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+# BERT Question and Answer
+
+Use a TensorFlow Lite model to answer questions based on the content of a given
+passage.
+
+Note: (1) To integrate an existing model, try
+[TensorFlow Lite Task Library](https://www.tensorflow.org/lite/inference_with_metadata/task_library/bert_question_answerer).
+(2) To customize a model, try
+[TensorFlow Lite Model Maker](https://ai.google.dev/edge/litert/libraries/modify/question_answer).
+
+## Get started
+
+<img src="images/screenshot.gif" class="attempt-right" style="max-width: 300px">
+
+If you are new to TensorFlow Lite and are working with Android or iOS, we
+recommend exploring the following example applications that can help you get
+started.
+
+<a class="button button-primary" href="https://github.com/tensorflow/examples/tree/master/lite/examples/bert_qa/android">Android
+example</a>
+<a class="button button-primary" href="https://github.com/tensorflow/examples/tree/master/lite/examples/bert_qa/ios">iOS
+example</a>
+
+If you are using a platform other than Android/iOS, or you are already familiar
+with the
+[TensorFlow Lite APIs](https://www.tensorflow.org/api_docs/python/tf/lite), you
+can download our starter question and answer model.
+
+<a class="button button-primary" href="https://tfhub.dev/tensorflow/lite-model/mobilebert/1/metadata/1?lite-format=tflite">Download
+starter model and vocab</a>
+
+For more information about metadata and associated fields (e.g. `vocab.txt`) see
+<a href="https://www.tensorflow.org/lite/models/convert/metadata#read_the_metadata_from_models">Read
+the metadata from models</a>.
+
+## How it works
+
+The model can be used to build a system that can answer users’ questions in
+natural language. It was created using a pre-trained BERT model fine-tuned on
+SQuAD 1.1 dataset.
+
+[BERT](https://github.com/google-research/bert), or Bidirectional Encoder
+Representations from Transformers, is a method of pre-training language
+representations which obtains state-of-the-art results on a wide array of
+Natural Language Processing tasks.
+
+This app uses a compressed version of BERT, MobileBERT, that runs 4x faster and
+has 4x smaller model size.
+
+[SQuAD](https://rajpurkar.github.io/SQuAD-explorer/), or Stanford Question
+Answering Dataset, is a reading comprehension dataset consisting of articles
+from Wikipedia and a set of question-answer pairs for each article.
+
+The model takes a passage and a question as input, then returns a segment of the
+passage that most likely answers the question. It requires semi-complex
+pre-processing including tokenization and post-processing steps that are
+described in the BERT [paper](https://arxiv.org/abs/1810.04805) and implemented
+in the sample app.
+
+## Performance benchmarks
+
+Performance benchmark numbers are generated with the tool
+[described here](https://www.tensorflow.org/lite/performance/benchmarks).
+
+<table>
+  <thead>
+    <tr>
+      <th>Model Name</th>
+      <th>Model size </th>
+      <th>Device </th>
+      <th>CPU</th>
+    </tr>
+  </thead>
+  <tr>
+    <td rowspan = 3>
+      <a href="https://tfhub.dev/tensorflow/lite-model/mobilebert/1/metadata/1?lite-format=tflite">Mobile Bert</a>
+    </td>
+    <td rowspan = 3>
+      100.5 Mb
+    </td>
+    <td>Pixel 3 (Android 10) </td>
+    <td>123ms*</td>
+  </tr>
+   <tr>
+     <td>Pixel 4 (Android 10) </td>
+    <td>74ms*</td>
+  </tr>
+   <tr>
+     <td>iPhone XS (iOS 12.4.1) </td>
+    <td>257ms** </td>
+  </tr>
+</table>
+
+\* 4 threads used.
+
+\*\* 2 threads used on iPhone for the best performance result.
+
+## Example output
+
+### Passage (Input)
+
+> Google LLC is an American multinational technology company that specializes in
+> Internet-related services and products, which include online advertising
+> technologies, search engine, cloud computing, software, and hardware. It is
+> considered one of the Big Four technology companies, alongside Amazon, Apple,
+> and Facebook.
+>
+> Google was founded in September 1998 by Larry Page and Sergey Brin while they
+> were Ph.D. students at Stanford University in California. Together they own
+> about 14 percent of its shares and control 56 percent of the stockholder
+> voting power through supervoting stock. They incorporated Google as a
+> California privately held company on September 4, 1998, in California. Google
+> was then reincorporated in Delaware on October 22, 2002. An initial public
+> offering (IPO) took place on August 19, 2004, and Google moved to its
+> headquarters in Mountain View, California, nicknamed the Googleplex. In August
+> 2015, Google announced plans to reorganize its various interests as a
+> conglomerate called Alphabet Inc. Google is Alphabet's leading subsidiary and
+> will continue to be the umbrella company for Alphabet's Internet interests.
+> Sundar Pichai was appointed CEO of Google, replacing Larry Page who became the
+> CEO of Alphabet.
+
+### Question (Input)
+
+> Who is the CEO of Google?
+
+### Answer (Output)
+
+> Sundar Pichai
+
+## Read more about BERT
+
+*   Academic paper: [BERT: Pre-training of Deep Bidirectional Transformers for
+    Language Understanding](https://arxiv.org/abs/1810.04805)
+*   [Open-source implementation of BERT](https://github.com/google-research/bert)