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Perform sentence filling and auto-complete using the DistilBERT natural language processing ML model. This package requires the open-source NatML and NatMLX libraries to run the machine learning model. Features include:
+ Bare Metal Performance. The DistilBERT language modeling predictor is implemented with NatML, which takes advantage of hardware machine learning accelerators, like CoreML on iOS and macOS, NNAPI on Android, and DirectML on Windows. View the model performance statistics on NatML Hub.
+ Extremely Easy to Use. The DistilBERT language modeling predictor accepts a sentence string with a special mask token, and returns the string with the mask token filled in with the best word that matches. As such, it can be used for auto-complete and other interactive applications. Read more here.
+ Cross Platform. The DistilBERT language modeling predictor supports Android, iOS, macOS, and Windows alike. As such you can test it in the Editor, and deploy it to the device all in one seamless workflow.
+ Lightweight Package. This package contains the predictor scripts, whereas the ML model will be downloaded at runtime from NatML Hub and cached onto the device, reducing the app size significantly.
Find other ML models on NatML Hub.
Join the NatSuite community on Discord.
Check out the NatML documentation.
See more NatSuite projects on GitHub.
Discuss NatML on Unity Forums.
Contact us at hi@natsuite.io.