I’ve used most of the high-end models in an unquantized format at some point or another (Xwin, Euryale, etc.) and found them generally pretty good experiences, but always seem to lack the ability to “show, not tell” in a way that a strong writer knows how to do, even when prompted to do so. At the same time, I’ve always been rather dissatisfied with a lot of quantizations, as I’ve found the degradation in quality to be rather noticeable. So up until now, I’ve been running unquantized models in 2x a100s and extending the context as far as I’m able to get away with.
Tried Goliath-120b the other day, and this absolutely stood everything on its head. Not only is it capable of stunning levels of writing and implying far more than directly stating in a way I’ve not sure I’ve seen in a model to date, but the exl quants from panchovix to get it to run in a single A100 at 9-10k extended context (about where RoPE scaling seems to universally start to break down in my experience). Best part is, if there is a quality drop (I’m using 4.85 bpw) I’m not seeing it - at all. So not only is it giving a better experience than an unquantized 70b model, but it’s doing so at about half the cost of my usual way of running these models.
Benchmarks be damned, for those willing to rent an A100 for their writing, however this model was managed I think this might be the actual way to challenge the big closed source/censored LLMs for roleplay.
Can we have some non-cherry-picked examples of writing?
Does not have to be highly nsfw/whatever, but a comparison of goliath writing compared to output from constituent models at same settings and same (well-crafted) prompts will be very interesting to see, and preferably at least 3 examples per model due to inherent randomness of model output…
If you say this is “night and day” difference, it should be apparent… I’m not sceptical per se, but “writing quality” is highly subjective and the model style may simply mesh better with your personal preferences?
I agree. We need at least some anecdotal evidence to back up the anecdotal claims. There’s one screenshot on the model page which looks fine (although it mixes past and present tense), but it’s not output you couldn’t get from a 7B model with some deliberate sampling choices and/or cherrypicking.
Yea, I’ve had my “honeymoon effect” with some new/large models like, say, Falcon and even Claude: they are inherently random and that affects quality, too. I’ve had great outputs from Falcon, for instance (on Petals), but also long stretches of mediocre and some outright bad… and also sometimes really great and creative output from 7b Mistral, especially with enough prompt tinkering and setting sampling “just right”. Objective evaluations of LMMs is extremely hard and time-consuming!