Tutorials

The full list of examples can be found in here. You can run each via python example/example-k.py. Most of examples require you to start a BertServer first.

Note

Although BertClient works universally on both Python 2.x and 3.x, examples are only tested on Python 3.6.

• Building a QA semantic search engine in 3 minutes
• Serving a fine-tuned BERT model
• Getting ELMo-like contextual word embedding
• Using your own tokenizer
• Using BertClient with tf.data API
• Training a text classifier using BERT features and tf.estimator API
• Saving and loading with TFRecord data
• Asynchronous encoding
• Broadcasting to multiple clients
• Monitoring the service status in a dashboard
• Using bert-as-service to serve HTTP requests in JSON