DealForge autonomously sources, scores, and writes investment memos on venture deals. Stop manually hunting.
1,180+ deals tracked · 22 AI investment memos · Updated daily
Show HN: Gemma 4 Multimodal Fine-Tuner for Apple Silicon
About six months ago, I started working on a project to fine-tune Whisper locally on my M2 Ultra Mac Studio with a limited compute budget. I got into it. The problem I had at the time was I had 15,000 hours of audio data in Google Cloud Storage, and there was no way I could fit all the audio onto my local machine, so I built a system to stream data from my GCS to my machine during training.<p>Gemma 3n came out, so I added that. Kinda went nuts, tbh.<p>Then I put it on the shelf.<p>When Gemma 4 came out a few days ago, I dusted it off, cleaned it up, broke out the Gemma part from the Whisper fine-tuning and added support for Gemma 4.<p>I'm presenting it for you here today to play with, fork and improve upon.<p>One thing I have learned so far: It's very easy to OOM when you fine-tune on longer sequences! My local Mac Studio has 64GB RAM, so I run out of memory constantly.<p>Anywho, given how much interest there is in Gemma 4, and frankly, the fact that you can't really do audio fine-tuning with MLX, that's really the reason this exists (in addition to my personal interest). I would have preferred to use MLX and not have had to make this, but here we are. Welcome to my little side quest.<p>And so I made this. I hope you have as much fun using it as I had fun making it.<p>-Matt
This is currently a technical side project rather than a venture-scale startup, addressing a specific gap in the Apple Silicon AI development ecosystem. While the developer shows strong engineering initiative by solving local memory constraints and multimodal fine-tuning gaps, it lacks a clear business model, team structure, or defensive moat.