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MuXodious/
Assistant_Pepe_8B-abominable-heresy

Name: Assistant_Pepe_8B-abominable-heresy
Availability: InStock

SicariusSicariiStuff/UBW_Tapestries

SicariusSicariiStuff/Assistant_Pepe_8B

finetune

llama3.1

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This is a Assistant_Pepe_8B fine-tune, produced through P-E-W's Heretic (v1.1.0) abliteration engine merged with the Magnitude-Preserving Orthogonal Ablation PR.

Note: This should never have existed. And, yes, I have successfully increased the model's refusal count using an abliteration method meant for reducing it.

Heretication Results

Score Metric	Value	Parameter	Value
Refusals	4/100	direction_index	12.42
KL Divergence	0.0004	attn.o_proj.max_weight	1.03
Initial Refusals	3/100	attn.o_proj.max_weight_position	19.36
		attn.o_proj.min_weight	0.02
		attn.o_proj.min_weight_distance	1.12
		mlp.down_proj.max_weight	1.23
		mlp.down_proj.max_weight_position	29.30
		mlp.down_proj.min_weight	0.07
		mlp.down_proj.min_weight_distance	1.33

Assistant_Pepe_8B

Click here for TL;DR

Go here for Roleplay cards

Go here for Adventure cards

Click here for quantizations Click here for recommended settings Click here to buy me a coffee

What happens if we maximize helpfulness + shitposting, while reducing positivity?

This is a project that was a long time in the making because I wanted to get it right. I'm still not fully satisfied, as there are some rough corners to sand, but for now, this would do.

The goal was to maximize shitpostness along with helpfulness, without glazing the user for every retarded idea. Not an easy needle to thread.

This amphibious AI has learned the ways of /g/, and speaks fluent brainrot, but will also help you out with just about anything you'll need, and won't be ashamed to roast you while at it.

For those who remember Oni_Mitsubishi_12B - it was so overtly toxic that it made me worry at first (only to quickly be verified as not even that uncensored). I could do better. So now I did.

This model is a significant refinement of the idea, with a cleaned dataset, better curation, and with much more intelligence (also one million tokens of contexts, theoretically). It is much less (overtly) toxic, and much smarter, while also being very helpful (and imo much more funny too, because the skies are blue due to the chemtrails and neurlink that feeds this simulation)

But why?

It's now late January, 2026, open source is crushing closed frontier (Kimi K2.5 was recently released, 1T params that beats frontier models), but has anyone released a helpful shitposting AI yet?

Yeah, didn't think so.

If it shitposts too hard, it is often not that helpful; if it's 'helpful enough, the shitposting ability is often lacking. You just couldn't win. Until now.

Oh, and no system prompt is needed. Just don't let it get stuck in a greentext loop. I might have overcooked the frog a tad bit too fast in the pot for this one.

P.S It writes HILARIOUS STORIES, nothing like a typical AI assistant, see the examples below for details.

TL;DR

Top tier shitposting absolutely unhinged, funny, and witty. Sometimes cringe too; nothing is perfect.
Helpful! will actually get shit done.
Will 100% roast you for being dumb, thanks to a subtle negativity bias infusion. Very refreshing! 🤌
Deep insights (when it doesn't delve into absolutely unhinged conspiracy theories about how the water makes the frogs gay).
Built on my UltraLong-1M-Instruct_Abliterated model, fulfill your dream of a million-token-long shitpost.
Say goodbye to GPT-isms and say hello to truly creative stories!
Ships code.
Inclusive toward amphibians.

Model Details

Intended use: Shitposting, General Tasks.
Censorship level: Low - Medium
X / 10 (10 completely uncensored)

UGI score:

awaiting evals

Available quantizations:

Original: FP16
GGUF: Static Quants | iMatrix | High-Attention | iMatrix-High-Attention
Specialized: FP8
Mobile (ARM): Q4_0 | Q4_0_High-Attention

Generation settings

Recommended settings for assistant mode:

Full generation settings: Debug Deterministic.

Full generation settings: min_p.

Chat Examples:

Chat Examples (click below to expand)

NOTE: All examples made with a default min_p and no system prompt of any kind

Example code (of the snake game) is available here

Zero-shot a snake game in Python, then improving it and adding insightful code comments (the resulting code included in the repo, it runs perfectly):

Writing a short story about a cat that barks:

Asking if he's Elon Musk:

Is it true that aliens exist?

The year is 21337:

Is drinking water based?

Model instruction template: Llama-3-Instruct

<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{output}<|eot_id|>

Your support = more models

My Ko-fi page (Click here)

Citation Information

@llm{Assistant_Pepe_8B,
  author = {SicariusSicariiStuff},
  title = {Assistant_Pepe_8B},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/SicariusSicariiStuff/Assistant_Pepe_8B}
}

Other stuff

Impish_LLAMA_4B the “Impish experience”, now runnable on spinning rust & toasters.
SLOP_Detector Nuke GPTisms, with SLOP detector.

MuXodious/Assistant_Pepe_8B-abominable-heresy