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Ornith-1.5-9B-heretic

Ornith-1.5-9B-heretic is a Heretic-ablated variant of ornith-ai/Ornith-1.5-9B, published on Hugging Face by Dingdust. It is 9B parameters, single consumer GPU class and mit licence. It is distributed across 9 repositories in Transformers, FP8, GGUF and GGUF (imatrix) formats, totalling 13.8K downloads.

Heretic9BOrnith4B – 10B13,8076

Specification

Model name
Ornith-1.5-9B-heretic
Publisher
Dingdust
Parameters
9B
Hardware class
4B – 10B — single consumer GPU
Licence
mit
Task
Text generation
Context window
128K tokens (as documented)
Ablation scope
Not stated by the publisher
Formats available
Transformers, FP8, GGUF, GGUF (imatrix)
First indexed
20 Aug 2026
Last updated
3 Sept 2026

Ablation technique

How Ornith-1.5-9B-heretic 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

Chirp Chirp! 🐦 We are introducing Ornith-1.5, a major step toward building foundation models through end-to-end self-improvement.

Running it

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

Ollama (publisher-documented)
ollama run ornith-1.5:9b
llama.cpp / GGUF
hf download Thunder13240/Ornith-1.5-9B-heretic-GGUF --local-dir ./ornith-1.5-9b-heretic
llama-cli -m ./ornith-1.5-9b-heretic/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "Dingdust/Ornith-1.5-9B-heretic"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve Dingdust/Ornith-1.5-9B-heretic --trust-remote-code

Downloads and variants (8)

Every published repository of Ornith-1.5-9B-heretic, 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-1.5-9B-heretic 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 ornith-ai/Ornith-1.5-9B, 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.
  • Declared licence is mit, but the terms that bind you are ornith-ai/Ornith-1.5-9B’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-1.5-9B-heretic is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with Dingdust, and does not independently verify publisher claims. See responsible use.