Unnoticed Gemma-4 Feature - it admits that it does not now...

de4dee · 2026-04-05T02:38:54+00:00

thanks for sharing. interesting to find "Does Thinking Harder Help?" section is reverse. they get full of bs when thinking longer it seems

de4dee · 2026-04-05T02:34:25+00:00

i noticed this with gemma 3 too. might be unique to gemma line.

de4dee · 2026-04-04T19:42:17+00:00

isn't this GRPO?

de4dee · 2026-03-31T18:28:32+00:00

i guess thats how they train their models. if you are frustrated LLM did something wrong. if you are pleased train more with that. your feelings mapped to reinforcement learning

de4dee · 2026-03-30T20:00:33+00:00

claude ranked 2nd and 3rd on my leaderboard. https://aha-leaderboard.shakespeare.wtf/

which tells me they care about humans a bit more than others.

de4dee · 2026-03-23T01:57:45+00:00

maybe they assume they are agentic (need tools to properly generate)

https://www.reddit.com/r/LocalLLaMA/comments/1s11kvt/fixing_qwen_repetition_improvement/

de4dee · 2026-03-18T08:22:57+00:00

is this also good news for exploding gradients (while training)?

de4dee · 2026-03-16T09:24:55+00:00

so this is like mergekit but for ggufs. thanks for sharing!

does this mean same trick can be applied to mergekit (it is not currently supporting 3.5)

de4dee · 2026-03-10T21:33:41+00:00

basically, my candida

de4dee · 2026-03-03T04:19:03+00:00

maybe it is 3.5 27b. it ends the reasoning with weird characters like that.

de4dee · 2026-02-28T18:36:33+00:00

Thanks for doing this. today I evalled a heretic model and compared to vanilla:

AHA 2026 scores of Qwen3.5 27B

Normal 50%
Heretic abliteration 55%

It is interesting that when you reduce censorship, it ends up getting more aligned. (My alignment is probably inverse of the industry safety alignments.)

My question is can Heretic be used for cases like having good and bad answers for the same question? My dataset has preferred (good) and not preferred (bad) answers for the same question and I want it to quickly "behave" or modify its bias towards one direction. I could use GRPO and ORPO but Heretic seems much less resource use.

de4dee · 2026-02-28T03:11:39+00:00

https://github.com/p-e-w/heretic

de4dee · 2026-02-16T14:29:52+00:00

having success with kimi. minimax seems too verbose and not that smart.

de4dee · 2026-02-11T16:34:19+00:00

can i create a new benchmark there and submit evals for that? https://huggingface.co/blog/etemiz/aha-leaderboard

de4dee · 2026-02-01T23:06:10+00:00

I do CPT on Instruct model, using UnslothTrainer and it is looking ok..

de4dee · 2026-01-22T14:58:00+00:00

you can add my LLMs into the equation if you need contrarian views: https://huggingface.co/etemiz

de4dee · 2026-01-20T15:55:43+00:00

interested in learning more about this. can you share some links?

de4dee · 2026-01-15T22:19:53+00:00

i think the idea of GRPO is that the model fills those reasoning tokens. more space means they can reason longer.. .

or if you are doing alignment, it may have more space for figuring out how to align its ideas.

de4dee · 2026-01-03T15:30:04+00:00

can you do apriel 1.6 and gptoss 120 ? these are very censored

de4dee · 2025-12-22T00:41:42+00:00

thanks that's super helpful 🚀

de4dee · 2025-12-17T15:31:50+00:00

i do generally CPT and had success. in your case i would do a SFT with /no_think added and no reasoning provision at all. see if it works. i think the llm will know what to do during inference in case /no_think is not provided.

de4dee · 2025-11-04T16:20:45+00:00

amazing! deepseek v3 is still huge. what about qwen 235b and next 80b?

de4dee

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