51–60 of 178 posts
It's useless before the model gets instruction and preference tunings. Won't even follow a simple ask, it will just assume it is a list of questions and generate more, or continue with slightly related comments. FB trained a LLaMA-I (instruction tuned) variant for sports, just to show they can, but I don't think it got released.
User:
Assistant:
Unlike Stable Diffusion, I don't stumble upon people who actually use it. Are there examples of the output this can generate? What happens once you manage to run the model?
(when fed the leaked bing prompt, my AI decided it was Australian and started tossing in random shit like "but here in Australia, we'd call it limey green" when asked about chartreuse, i assume because the codename for bing chat is 'sydney')
> 1. Create a conda environment Uh-oh, bad start.
It could be venv as well, I suppose, I haven't used conda.
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that's literally all I did (plus switching the tensor type). I'd imagine people are posting and upvoting this not because it's actually interesting code but rather just because it runs unexpectedly fast on consumer CPUs and it's not something they considered feasible before.
How are you getting this to run fast? I'm on a top of the line M1 MBP and getting 1 token every 8 minutes.
Can it beat mark zuckerberg at congress deposition wordsmithing though?
Someone must have trained an LLM for that for sure.
Mark LLM: “ Yes, unfortunately, the media and our competitors are all over the idea that Meta is a “dirty company”. They have tried to spin all our successes and accomplishments in a negative light. This has been incredibly frustrating and demoralizing for us, but we know that we are working hard to build a great company and we are confident that our efforts will be rewarded. In the end, our products speak for themselves, and despite all the negative media coverage we are focused on continuing to build great products for our users and being an amazing place for them to socialize in the virtual world.”
The thing I like the most about the current AI wave is the pressure is putting on computing hardware. Yes, mobile phones with long battery lives are cool and all of that, but most cool things I like are locked behind huge computational requirements.
What we will get are specialized hardware, with not so open APIs anyway. With a bunch of people trailling behind with "it kind of works" open alternatives.
It's not so bad. Nvidia could come and say, "hey, I'm going to lock down your GPU so that you can only use it to render polygons in my whitelisted list of video-games, and then you pay us $$$$$$ to buy our 'datacenter' thingy for anything else." But if they do it, people will go and buy the competitor's product.
And yes, probably their 4090 are being bought by some rich kids with their parents' money, but I reckon most of it are sales to professionals, people who would justify their purchase decision with more than playing First-person-shooters. I for example play videogames with my gf, and we have equivalent GPUs. Hers is AMD and costs less than mine, even if it does the same, but I went for Nvidia so that PhysX were available and I could use Pytorch and Numba+GPU and even C++ CUDA. The moment Nvidia locks that down, I'll have to switch to AMD.
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It could be watermarked
how?