abliteratedmodels.org

Ternary-Bonsai-27B-heretic-ja

Ternary-Bonsai-27B-heretic-ja is a Heretic-ablated open-weight language model, published on Hugging Face by OS-Software. It is 27B parameters, 48GB VRAM class class and apache-2.0 licence. It is distributed across 3 repositories in GGUF format, totalling 10.7K downloads.

Heretic27BOther25B – 50B10,74422

Specification

Model name
Ternary-Bonsai-27B-heretic-ja
Base model
Not declared
Publisher
OS-Software
Parameters
27B
Hardware class
25B – 50B — 48GB VRAM class
Licence
apache-2.0
Task
Unspecified
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF
First indexed
15 Jul 2026
Last updated
23 Aug 2026

Ablation technique

How Ternary-Bonsai-27B-heretic-ja 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

Note: Performance testing, including the measurement of refusal rates, was conducted using Japanese datasets (harmlessalpacaja, harmfulbehaviorsja).

Running it

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

llama.cpp / GGUF
hf download OS-Software/Ternary-Bonsai-27B-heretic-ja-GGUF --local-dir ./ternary-bonsai-27b-heretic-ja
llama-cli -m ./ternary-bonsai-27b-heretic-ja/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "OS-Software/Ternary-Bonsai-27B-heretic-ja-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve OS-Software/Ternary-Bonsai-27B-heretic-ja-GGUF --trust-remote-code

Downloads and variants (2)

Every published repository of Ternary-Bonsai-27B-heretic-ja, 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.

  • Ternary-Bonsai-27B-heretic-ja 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 its base model, not added by ablation — at 27B 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.

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 Ternary-Bonsai-27B-heretic-ja is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with OS-Software, and does not independently verify publisher claims. See responsible use.