alt Hacker NewsGemma 4 is a strongly censored model, so much so that it refused to answer medical and health related questions, even basic ones. No one should be using it, and if this is the best that Google can do, it should stop now. Other models do not have such ridiculous self-imposed problems.
Replies
I don't quite get why you feel so strongly about it that this should be a deal breaker for everyone. It's really much better than a wrong answer, for everyone.
I suspect a possible future of local models is extreme specialisation - you load a Python-expert model for Python coding, do your shopping with a model focused just on this task, have a model specialised in speech-to-text plus automation to run your smart home, and so on. This makes sense: running a huge model for a task that only uses a small fraction of its ability is wasteful, and home hardware especially isn't suited to this wastefulness. I'd rather have multiple models with a deep narrow ability in particular areas, than a general wide shallow uncertain ability.
Anyway, is it possible that this may be what lies behind Gemma 4's "censoring"? As in, Google took a deliberate choice to focus its training on certain domains, and incorporated the censor to prevent it answering about topics it hasn't been trained on?
Or maybe they're just being sensibly cautious: asking even the top models for critical health advice is risky; asking a 32B model probably orders of magnitude moreso.
There are uncensored / "abliterated" / heretic versions available on Huggingface.
You can get abliterated versions that have no (or very limited) refusals.
I tend to use Huihuiai versions.
Weird. A great number of my medical or legal queries are actually answered, but come with a disclaimer, often at the end of the inference. (I'd offer up some examples, but I'm not at the desk.)
I also find that you can coerce a wide spectrum of otherwise declined queries by editing its initial rejection into the start of an answer. For example changing the "I'm sorry I can't answer that..." response to "Here's how..." And then resubmitting the inference, allowing it to continue from there. It's not perfect, sometimes it takes multiple attempts, but it does work. At least in my experience. (This isn't Gemma-specific tip, either. Nearly every model I've tried this with tends to bend quite a bit doing this.)
Since it's open weights there's nothing stopping you from grabbing one of the uncensored variants from huggingface.co