this post was submitted on 12 Nov 2024
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[–] [email protected] 11 points 3 days ago* (last edited 3 days ago) (6 children)

To add to this:

All LLMs absolutely have a sycophancy bias. It's what the model is built to do. Even wildly unhinged local ones tend to 'agree' or hedge, generally speaking, if they have any instruction tuning.

Base models can be better in this respect, as their only goal is ostensibly "complete this paragraph" like a naive improv actor, but even thats kinda diminished now because so much ChatGPT is leaking into training data. And users aren't exposed to base models unless they are local LLM nerds.

[–] [email protected] 2 points 2 days ago (3 children)

One of the reasons I love StarCoder, even for non-coding tasks. Trained only on Github means no "instruction finetuning" bullshit ChatGPT-speak.

[–] [email protected] 2 points 2 days ago (2 children)

People still run or even continue pretrain llama2 for that reason, as its data is pre-slop.

[–] [email protected] 1 points 2 days ago (1 children)

I really wish it were easier to fine-tune and run inference on GPT-J-6B as well... that was a gem of a base model for research purposes, and for a hot minute circa Dolly there were finally some signs it would become more feasible to run locally. But all the effort going into llama.cpp and GGUF kinda left GPT-J behind. GPT4All used to support it, I think, but last I checked the documentation had huge holes as to how exactly that's done.

[–] [email protected] 1 points 2 days ago

Still perfectly runnable in kobold.cpp. There was a whole community built up around with Pygmalion.

It is as dumb as dirt though. IMO that is going back too far.

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