How do I deploy a model using TensorFlow Serving?
An example of an AI chatbot conversation about deploying models with TensorFlow Serving API.
How do I deploy a model using TensorFlow Serving?
To deploy a model using TensorFlow Serving, you first need to save your model in the TensorFlow SavedModel format.
What are the steps to save my model in the SavedModel format?
You can save your model using tf.saved_model.save(model, export_dir) where model is your trained model and export_dir is the directory to save it.
How do I start the TensorFlow Serving server?
You can start the server using the command: tensorflow_model_server --rest_api_port=8501 --model_name=my_model --model_base_path=/path/to/model.
Can I deploy multiple models at once?
Yes, you can deploy multiple models by specifying different model names and base paths in the server command.
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