There are now 5 inference providers for abliterated DeepSeek

In case it wasn't clear to anyone else: "An abliterated model is an open-weight large language model (LLM) modified to remove its built-in refusal behavior by directly editing its internal weights rather than using a prompt-based jailbreak."

From my testing all these variants suffer from degraded performance and don't unlock anything interesting in particular other than sounding a lot more harmful or creating manipulative media.

I've actually had better success jailbreaking deepseek with a less aligned model (glm 5.2) which then allowed me to jailbreak deepseek with deepseek into pretty much doing whatever I ask it to, there's still rare refusals and due to the natural randomness of these models simply retrying a couple of times if you do hit one makes it work just fine.

The big problem with all open-source models is once it decides to start something it will not stop mid-way so using another unaligned model to rewrite reasoning and then feeding it back into the model will make it happily continue.

I genuinely do not see why this is necessary. I've been doing a lot with open weights models, and they just do things for you.

What do people do that triggers refusals?

The only thing I saw where this had a point was muse glimmer, because muse glimmer is primarily a creative writing engine for virtual characters, and that way it can do the horny. But coding models?

I did get a refusal out of qwen once. Once. Over weeks of using it.

This thread reminds me of the time I was trying to learn meteorjs and people ask me if it has html5 shims. I google it, then I get asked how does it handle state, and if it supports functional, i google... Does it hydrate the dom? What about shadow dom? Let me goo... Does it have hooks?

Anyway, I just learned what abliterated means and it might be obsolete by tomorrow.

Edit:

> An abliterated large language model (LLM) is an open-weight model modified to remove or dampen its built-in safety refusals without requiring full retraining or prompt jailbreaks.

Has anyone already seen a refusal from Deepseek? The last job, Antigravity declined, I gave to Deepseek. It happily did it without complaining.

Which if not all of these are honeypots?

That is a good idea for an authorities honeypot.

Why not just distribute the refusal vectors and do it at runtime against the stock model?

What is abliteration?

https://huggingface.co/blog/mlabonne/abliteration

Morph is hosting this as well

As it should be.

Looks like the cat is out of the bag. So what does the world look like with completely open access to zero-alignment models?

I suppose in some contexts, refusals are a bad thing.

But if you're doing anything where your AI agent might get exposed to a prompt injection attack, you might prefer it to do a refusal in that case.

What could possibly go wrong with highly powerful models with no guardrails unleashed onto the open internet?

I think you are going to really need to use Rust code and other memory safe languages in your backends and apps from now on.