![]() Imagine being able to take some newly released research and make that model available to millions of JS developers globally. Understand what to do when something goes wrong (not all models will convert) and what options you have.Take the resulting files from conversion and use in your JS web application.How to install and use the TensorFlow.js converter on the SavedModel you exported from Python.How to create a simple Python ML model and save it to the required format needed by the TensorFlow.js converter.In this code lab you will learn how to use the TensorFlow.js command line converter to port a Python generated SavedModel to the model.json format required for execution on the client side in a web browser. ![]() The TensorFlow.js team have made a convenient tool to convert models that are in the SavedModel format to TensorFlow.js via a command line converter so you can enjoy using such models with the reach and scale of the web. Sound familiar? If so, this is the CodeLab for you! So you've taken your first steps with TensorFlow.js, tried our pre-made models, or maybe even made your own - but you saw some cutting edge research come out over in Python and you are curious to see if it will run in the web browser to make that cool idea you had become a reality to millions of people in scalable way. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |