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From the video output seems fine.

But if it is a trimmed version, it is wong to call it LLaMa.



Could call it Slim LLaMa


SLLaMa?


It's nonsensical, celeb announces they're going to rehab and notes it (?) is an issue affecting all women, at least, earlier today (??), they also noted it wasn't drugs or alcohol this time, but, a life (???)


Without instruction tuning, the perfect language model produces output which has the same level of intelligibility as random text from the training set. And the training set probably has a lot of spam and junk in.


What are you comparing it to? Without instruction tuning and a two character prompt "He" I am not sure why you would expect it to perform any better.


I was replying to a comment that said it “seems fine.”

It does not seem fine.

It is incomprehensible and doesn’t match the results I’ve seen from 7B through 65B.

It is true that RLHF could improve it, and perhaps then this severe of optimization will seem fine.


I've heard a number of people say (from earlier) that the quantization and default sampling parameters is way wacked. Honestly even running that model size alone is the big achievement here and getting the accuracy to actually reach the benchmark is the beeg next step nao, I believe. <3 :'))))


If you run a quantized 60G model and the output is worse than raw 7G model, you can throw your quantizer out.




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