Project case study
Can I run this Hugging Face model?
Hardware-aware AI model compatibility checker for local inference
Browser-based compatibility checker that detects device hardware, fetches Hugging Face model metadata, estimates VRAM and RAM needs, and tells you whether a local run looks great, tight, or too heavy.
Problem
People exploring local AI models often do not know whether a model will run on their laptop, browser, or GPU before downloading it. That creates friction, failed experiments, and unnecessary support questions.
Solution
I built a browser-first checker that inspects device hardware, reads model metadata, estimates memory requirements, and translates the result into clear compatibility guidance for real users.
Impact
The result is a faster discovery flow for local AI users and a cleaner way to explain model requirements without making people decipher raw specs on their own.
Stack and implementation notes
This project combines product thinking with technical implementation. The goal was not only to prove the underlying model or workflow, but to shape it into something understandable and usable for real people.
Technologies used here include Astro, TypeScript, Web APIs, Hugging Face metadata, WebGPU heuristics. The stack was chosen to keep the delivery practical while still leaving room for experimentation, iteration, and deployment.