That’s exciting, but if the future of AI only belongs to people with massive compute, then it is not really for everyone.
That’s why the Hugging Face smol models event matters.
Small models are not just tiny versions of big models. They are the models that can run cheaper, faster, closer to the user, and eventually on normal machines.
That is the lane I’m building in.
I’m working on a rewrite model series for messy real-world input:
voice transcripts, rambling thoughts, half-correct instructions, and all the “no wait, actually…” moments where the intent is there, but buried.
A giant model can clean that up.
Cool.
I want small open models to get better at it too.
Current goal:
$54.43/month Colab Pro+ + fees 11% funded
That lets me iterate faster with better datasets, techniques, and compute. Yep.
If you care about useful small models and open experimentation, even $1 helps:
If you don't understand what you see, this is just one the coolest proof of concepts I've ever made. I just trained a char-level, super small model (~80 million parameters) on millions of high-quality examples on a curated dataset and is slowly getting davinci-003 vibes
As an advocate for small language models I just want to say. It might not actually be the end for small models. We are just getting started! Now that we have super good models we can find creative ways to replicate the behavior at small scale!
I'll show you in a few weeks what a small model is capable of, you will surprised.
Cheers for a year of sota AI on cpus 🥂 people actually liked my last model, here's another sota for you. This one should feel way different in terms of quality.