alt Hacker NewsI run an abliterated distillation of Qwen 3.8 27B, slightly quantized to fit on my 4090, and I've been evaluating it to use as a worker bee for research directed by a smarter model.
Much like in the article, abliterated Qwen will not obey restrictions on its behavior encoded in the prompt. If you want something not to happen, it better be enforced in the harness or environment (e.g. sandbox). It is much different than the Anthropic models I'm used to, which will, the vast majority of time, follow rules (before auto mode, I used to always run them in "yolo" mode).
I am curious whether there's a connection between abliteration and rule following. These abliterated models are the ones you most want to follow your rules.
Language models have always had an issue with negatives.
A negative like do “not” xyz is just not encoded the same as spelling out what you want vs what you don’t want.
Harder to write though.