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Comment by sp332 | Hacker News Reader

ChatGPT had an estimated 20,000 hours of human feedback. That’s not going to be easy to replicate in an open source way.

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OpenAssistant has already collected 100,000 human feedback examples, estimated 5,000+ hours of human work via crowd sourced volunteers.

Enough programmers want this badly enough that its going to happen. Inference at 8 GB and fine tuning at 24 GB, just like stable diffusion, on a 13B model.

From what I gather, tuning a language model is like jury duty: The more eager someone is to volunteer, the less useful his input is going to be.

I don't think the quality of the OpenAssistant data represents that idea at all.

This sounds incredibly hard to believe, unless your concern is that advertisers will poison the well.

Is it that hard to believe? If you look at Stable Diffusion, I'd say a lot, maybe the majority of the volunteer effort was focused on anime girls and "realistic" pictures of anime girls (which amounts to young faces on adult bodies).

That's the next level up from instruction tuning though: that was the RLHF stuff, which was essential to make ChatGPT useful and safe enough to expose to a wide audience.

For a model running on my own laptop I'm OK taking more risks. I'd like it to be able to obey simple instructions like "Summarize this text" or "Extract the names of everyone mentioned in this article" - I don't care as much about the stuff ChatGPT has to get right.

Perhaps we will provide feedback to open source Llama using ChatGPT. The cost to adjust the model is presumably what's hard?

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