Using On-Demand GPUs to Build and Deploy ML Models with Hex and Modelbit

This post details the integration of Hex with Modelbit to leverage on-demand GPUs for ML model training and deployment. It demonstrates a workflow where a Grounding DINO model is built and trained using Modelbit's remote GPU compute, orchestrated from a Hex notebook. The trained model is then deployed as a REST API via Modelbit, and inference requests are made back to the Hex project. This showcases an end-to-end ML workflow within Hex, utilizing external GPU resources for computationally intensive tasks.