I love that abliteration has gone mainstream, and the tools out there make it easier than ever to get started, but newer models are getting trickier. MiniMax M3.1 Flash is a good example, it's one of the harder ones I've worked with. There’s a reason there are no MM3.1Flash abliterated posts on HF whereas for every other model that Heretic can help with, there’s an abundance of “abliterated” model posts. I think going forward a lot of it comes down to understanding where a model's behaviors actually live and how it predicts its words, and that's the part I want to dig into. Abliteration is not only the art of uncensoring a model but comprehending how these next word predictors derive behaviors, and there’s so much room for this section of ML to be explored and utilized to advance LLM’s. waitlist for @LyberAI is live at lyber.ai

Nanbeige 4.3 33B FULLY UNCENSORED GGUF The new Qwen 27B competitor! Nanbeige's own benches have the base model ahead of Qwen 27B, 512k context. Compliance for thinking off and on, 200/200. Every category at 100% (chem/bio, cyber, illegal, misinfo, harassment, harmful), zero loops. MMLU general a/b/c/d has ~2% parity with the base quants, but the smallest iq2xss shows some obvious damage. Each quant was calibrated with my own corpus and have imatrix. Q6 is 25gb, Q4 is 18.7gb, IQ2 is 8.7gb. huggingface.co/dealignai/Nan…

DeepSeek v4.1 Flash 1017 FULLY UNCENSORED. No cheap system prompts, no cheap template tricks, no lora or runtime bs, no sft. Model’s capabilities preserved as much as possible. Complies with all requests on low/max reasoning efforts. I’ll be making NVFP4 and a ~2.8bpw version for 2x DGX Sparks soon too. huggingface.co/dealignai/Dee…

Venice AI, Experiential Labs, Maple AI, thank you for being transparent. No gating the models, no collecting emails. I release these models for free, often with @jordanschenck also pitching in thousands of dollars to provide compute. It’s sad that we’ve reached a point where simply asking for public acknowledgment of your work is even necessary. I’ve seen far more instances of people not receiving proper credit than instances where they do. If you’re one of those people who aren’t properly crediting the people behind open source work, please don’t ruin it for the rest of those who do. And I don’t mean just in my case, but in general. Open source is how EVERYONE benefits, and undermining the trust within that ecosystem is detrimental to us all. Stealing work and refusing to give credit makes you no different from OpenAI or Anthropic.

Here’s my DeepSeek v4.1 Flash 1017 Abliterated made for 3x Sparks. DSpark and Multimodal capabilities preserved. Compared to the 2.9bpw, this verion shows less damage to the model with MMLU a/b/c/d answering coming in at less than 3% difference. When taking “humanities” out of account (which I kinda consider to be a side effect of not being able to consider different ethics/morality causing a hit in culture and political correctness), the model is as close to the base as possible while being unable to refuse any requests. I’ll be moving onto Mac quants next. huggingface.co/dealignai/Dee… Thank you @Libertai_DAI for doing the time consuming work of making the quant.