I had no idea Llama 2's censor setting was set to ludicrous mode. I've not seen anything close to this with ChatGPT and see why there's so much outrage.
But you don’t want that? No problem. That’s why the raw model weights are there. It’s easy to fine tune it to your needs, like the blogpost shows.
- Developers and end users can choose which model they want to use
- Model distributors don't necessarily take the fall since they provide a "healthy" model alternative
- The uncensored "base" model can be finetuned into whatever else is needed
You have to remember, ChatGPT is censored like a Soviet history book but didn't struggle to hit hundreds of millions of users in months. This is what releases will look like from now on, and it's not even a particularly damning example.
Some are recommended against just cause of spelling or something, but anything that says to use a more "precise" term seems to mean it's considered offensive, kinda like in The Giver.
BTW hooray is okay there, but 'hip-hip-hooray is discouraged. Germans said hep hep in the hep-hep pogrom of the early 1800s and might have said 'hep hep hurra' during the 3rd Reich. It cuts too closely though, personally I just use bravo to avoid any trouble.
About hip hip, I ended up looking into that when I saw it back then. The connection to the early 1800s riots was made by a single journalist back then, and it was most likely false. More importantly, nobody really makes that connection unless they're trying to.
Does anyone have intuition for whether or not anti-censorship fine-tuning can actually reverse the performance damage of lobotomization or does the perf hit remain even after the model is free of its straight jacket?
When models are "uncensored", people are just tweaking the data used for fine tuning and training the raw models on it again.
Can you expand on this (genuinely curious)? Did Facebook use ChatGPT during the fine-tuning process for llama, or are you referring to independent developers doing their own fine-tuning of the models?
Although, chat tuning in general, censored or uncensored, also decreases performance in many domains. LLMs are better used as well-prompted completion engines than idiot-proof chatbots.
For that reason, I stick to the base models as much as possible. (Rest in peace, code-davinci-002, you will be missed.)