3 ms·
I've never gotten incorrect answers faster than this, wow! Jokes aside, it's very promising. For sure a lucrative market down the line, but definitely not for
by baalimago 8mo ago
I've never gotten incorrect answers faster than this, wow!
Jokes aside, it's very promising. For sure a lucrative market down the line, but definitely not for a model of size 8B. I think lower level intellect param amount is around 80B (but what do I know). Best of luck!
- Derbasti 8mo agoAmazing! It couldn't answer my question at all, but it couldn't answer it incredibly quickly! Snarky, but true. It is truly astounding, and feels categorically different. But it's also perfectly useless at the moment. A digital fidget spinner.
- anthonypasq 8mo agodoes no one understand what a tech demo is anymore? do you think this piece of technology is just going to be frozen in time at this capability for eternity? do you have the foresight of a nematode?
- edot 8mo agoYeah, two p’s in the word pepperoni …
- PlatoIsADisease 8mo agoAs someone with a 3060, I can attest that there are really really good 7-9B models. I still use berkeley-nest/Starling-LM-7B-alpha and that model is a few years old. If we are going for accuracy, the question should be asked multiple times on multiple models and see if there is agreement. But I do think once you hit 80B, you can struggle to see the difference between SOTA. That said, GPT4.5 was the GOAT. I can't imagine how expensive that one was to run.
- otabdeveloper4 8mo agoMake it for Qwen 2.5 and I'd buy it. You don't actually need "frontier models" for Real Work (c). (Summarization, classification and the rest of the usual NLP suspects.)
- SkyPuncher 8mo agoI completely agree. So many things can benefit from having "smart classifiers". Like, give me semantic search that can detect the difference between SSL and TLS without needing to put a full LLM in the loop.