This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass 🌿
💡 The idea in one breath
Most weather apps...
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How often do you retrain the TabPFN model with new weather data to keep the predictions up‑to‑date?
TabPFN fits at startup on our ERA5 history CSV; today's weather row is fetched live from Open-Meteo per request. Full dataset refresh = re-run fetch_real_data.py + redeploy. No scheduled retrain yet; that's a solid v2 idea.
thanks
Nice Work!
Nice build.
Great Build!!
solid work!
Really thoughtful post! Documenting real-world engineering hurdles and actionable solutions like this brings immense value to the community.
thanks, it means a lot
Great project 👍
Impressive !
Great work! The project looks impressive. 👏