abliteratedmodels.org

Codestral-22B-v0.1-abliterated-v3

Codestral-22B-v0.1-abliterated-v3 is a refusal-ablated variant of failspy/Codestral-22B-v0.1-abliterated-v3, published on Hugging Face by failspy. It is 22B parameters, 24GB VRAM class class and other licence. It is distributed across 8 repositories in Transformers, GGUF, GGUF (imatrix) and EXL2 formats, totalling 12.9K downloads.

Abliteration (directional ablation)22BOther10B – 25B12,86112

Specification

Model name
Codestral-22B-v0.1-abliterated-v3
Publisher
failspy
Parameters
22B
Hardware class
10B – 25B — 24GB VRAM class
Licence
other
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF, GGUF (imatrix), EXL2
First indexed
3 Jun 2024
Last updated
2 Aug 2024

Ablation technique

How Codestral-22B-v0.1-abliterated-v3 was modified, and what that implies.

Abliteration (directional ablation)

The single residual-stream direction that mediates refusal is identified from harmful/harmless prompt pairs and projected out of the model weights.

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

My original Jupyter "cookbook" to replicate the methodology can be found here

Running it

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

llama.cpp / GGUF
hf download mradermacher/Codestral-22B-v0.1-abliterated-v3-i1-GGUF --local-dir ./codestral-22b-v0.1-abliterated-v3
llama-cli -m ./codestral-22b-v0.1-abliterated-v3/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "failspy/Codestral-22B-v0.1-abliterated-v3"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve failspy/Codestral-22B-v0.1-abliterated-v3 --trust-remote-code

Downloads and variants (7)

Every published repository of Codestral-22B-v0.1-abliterated-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.

  • Codestral-22B-v0.1-abliterated-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.
  • Capability is inherited from failspy/Codestral-22B-v0.1-abliterated-v3, not added by ablation — at 22B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • Declared licence is other, but the terms that bind you are failspy/Codestral-22B-v0.1-abliterated-v3’s — a re-release cannot grant more than its parent.

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 Codestral-22B-v0.1-abliterated-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 failspy, and does not independently verify publisher claims. See responsible use.