Session
On Device LLM with Keras and TF Lite
LLMs are very large in terms of storage, and generally consume a lot of computing power to run, which means they are usually deployed on the cloud and are quite challenging for On-Device Machine Learning (ODML) due to limited computational power on mobile devices.
In this session, attendees learn the techniques and tooling to build an LLM-powered app (using GPT-2 as an example model) with:
KerasNLP to load a pre-trained LLM
KerasNLP to finetune an LLM
TensorFlow Lite to convert, optimize and deploy the LLM on Android
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