Fine-tune AI models on your data — in minutes, not days.
FineTuner trains your own AI on your content (PDF, YouTube videos, websites...) without writing a single line of code. Generate a high-quality dataset, fine-tune your model (GPT or Claude), and deploy it via API ready to use in minutes.
I’ve always dreamed of an AI that could absorb my own content and speak in my exact voice. Two months ago I finally asked Cursor:
“Can you write a script that automates fine-tuning GPT-4o on my own content?”
That innocent prompt kicked off an 8-week rabbit-hole: 100+ workflows tested, 16-hour days, $250 in OpenAI bills, countless Docker tantrums. I’m a low-code guy, so I had to learn real backend stuff on the fly—async Python, routing, deployments, the lot. Every time the AI “almost” worked, dopamine kept me glued to the screen.
Yesterday the last bug finally gave in. The result is Finetuner:
⚡ What it does ⚡
Point it at your Docs, PDF, YouTube, websites — anything.
In minutes you get a fully fine-tuned GPT-4o (or Claude) that speaks exactly in your voice.
No YAML rituals, no JSON wrangling. Just upload, click, done.
🛠 Why it’s different 🛠
Built 100 % with Cursor. Yes, the same AI that writes the code now teaches your model.
Handles the whole pipeline: data scraping ➜ cleaning ➜ training ➜ validation ➜ ready-to-use API.
Works for clones (“Tweet like Steve Jobs”) or personal brands (your unique tone).
I’d love feedback from the PH community: features you’d want, edge-cases you’re worried about, or horror stories from your own fine-tuning adventures. Drop a comment or DM me. Happy to share the gritty details of building a “real” app entirely with AI.
Thanks for hunting, and may the (Force) fine-tunes be with you!
