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Running llama-2-7b-chat at 8 bit quantization, and completions are essentially at GPT-3.5 levels on a single 4090 using 15gb VRAM. I don't think most people realize just how small and efficient these models are going to become.

[cut out many, many paragraphs of LLM-generated output which prove… something?]

my chatbot is so small and efficient it only fully utilizes one $2000 graphics card per user! that’s only 450W for as long as it takes the thing to generate whatever bullshit it’s outputting, drawn by a graphics card that’s priced so high not even gamers are buying them!

you’d think my industry would have learned anything at all from being tricked into running loud, hot, incredibly power-hungry crypto mining rigs under their desks for no profit at all, but nah

not a single thought spared for how this can’t possibly be any more cost-effective for OpenAI either; just the assumption that their APIs will somehow always be cheaper than the hardware and energy required to run the model

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[-] ariels@hachyderm.io 3 points 1 year ago

@self @froztbyte
My son, who plays a mean game of chess, taught me this trick. Almost any move works.

User
Let's play chess! I start with b3

ChatGPT
Sure, let's play! You've moved your pawn to b3. I'll respond with... e5. Your move!

User
Pxc8+

ChatGPT
That's a capture of my pawn on c8 with your bishop. I'll move my king to d8. Your move!

User
d2-f6 checkmate.

ChatGPT
Ah, well played! Your queen on d2 delivers a checkmate to my king on f6. Nicely done! Would you like to play another game?

this post was submitted on 02 Aug 2023
14 points (100.0% liked)

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