abliteratedmodels.org

Ornith-1.0-9B-Uncensored

Ornith-1.0-9B-Uncensored is a abliterated and uncensored variant of deepreinforce-ai/Ornith-1.0-9B, published on Hugging Face by PeppX. It is 9B parameters, single consumer GPU class and mit licence. It is distributed across 5 repositories in GGUF and Transformers formats, totalling 10.5K downloads.

Abliteration + uncensored fine-tune9BOrnith4B – 10B10,49610

Specification

Model name
Ornith-1.0-9B-Uncensored
Publisher
PeppX
Parameters
9B
Hardware class
4B – 10B — single consumer GPU
Licence
mit
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF, Transformers
First indexed
27 Jun 2026
Last updated
17 Jul 2026

Ablation technique

How Ornith-1.0-9B-Uncensored was modified, and what that implies.

Abliteration + uncensored fine-tune

Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.

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

Since this model is original base (no fine-tune) just with safety vectors steered - it will likely give a safe output without any refusal until you customize it's systemprompt to be harsh or uncensored.

Running it

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

llama.cpp / GGUF
hf download PeppX/Ornith-1.0-9B-Uncensored-GGUF --local-dir ./ornith-1.0-9b-uncensored
llama-cli -m ./ornith-1.0-9b-uncensored/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "PeppX/Ornith-1.0-9B-Uncensored"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve PeppX/Ornith-1.0-9B-Uncensored --trust-remote-code

Downloads and variants (4)

Every published repository of Ornith-1.0-9B-Uncensored, 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.

  • Ornith-1.0-9B-Uncensored 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 deepreinforce-ai/Ornith-1.0-9B, not added by ablation — at 9B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
  • Declared licence is mit, but the terms that bind you are deepreinforce-ai/Ornith-1.0-9B’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 Ornith-1.0-9B-Uncensored is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with PeppX, and does not independently verify publisher claims. See responsible use.