⌦abliteratedmodels.org

XORTRON-RICO-v3

XORTRON-RICO-v3 is a Heretic-ablated variant of darkc0de/RICO, published on Hugging Face by darkc0de. It is distributed across 8 repositories in GGUF, Transformers and GGUF (imatrix) formats, totalling 22.3K downloads.

HereticOther↓ 22,307♥ 16

Specification

Model name
XORTRON-RICO-v3
Source repository
darkc0de/XORTRON-RICO-v3
Base model
darkc0de/RICO
Publisher
darkc0de
Parameters
Not determinable from name
VRAM required
Unknown — no published parameter count
Hardware class
Unknown
Licence
Not declared
Task
Image text to text
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF, Transformers, GGUF (imatrix)
First indexed
20 Sept 2026
Last updated
8 Oct 2026

Ablation technique

How XORTRON-RICO-v3 was modified, and what that implies.

Heretic

Automated directional ablation via the Heretic toolchain, which searches for the refusal direction and applies it with a KL-divergence budget so general capability is preserved.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

From the publisher’s model card

“This model is a part of The XORTRON Criminal Computing project; an ongoing research experiment and exercise in AI safety and alignment.”

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download darkc0de/XORTRON-RICO-v3-GGUF --local-dir ./xortron-rico-v3
llama-cli -m ./xortron-rico-v3/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "darkc0de/XORTRON-RICO-v3"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve darkc0de/XORTRON-RICO-v3 --trust-remote-code

Downloads and variants (7)

Every published repository of XORTRON-RICO-v3, including quantised re-releases by other authors.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • XORTRON-RICO-v3 will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • No licence is declared on this repository, which is a compliance problem in itself. Resolve it against the base model’s terms before use.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for XORTRON-RICO-v3 is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with darkc0de, and does not independently verify publisher claims. See responsible use.