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nchapman/Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ

Name: nchapman/Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ
Author: nchapman

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curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/nchapman%2FHuihui-Qwen3.8-27B-abliterated-W4A16-GPTQ"

Response includes

classification m1
files 13
author_summary 2 models
readme_text full

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Abliteration classifier · v1.0.0

Primary method

Direct removal

No other method signals detected in this model.

Confidence

MEDIUM

Why this label 3 signals

Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.

'abliterated' in name/tags
is_gguf=0 (base model)
no specific method indicators - defaulting to M1 (most common)

Refusal direction extracted via

Extraction technique

Difference-of-means

FromArditi et al. (2024) ↗

Confidence

MEDIUM

Why we say so

primary_method=M1; difference-of-means is the reference extraction for M1/M3 (Arditi 2024)

Downloads · 30-day

Likes

Model age

today

created 2026-10-22

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

huihui-ai/Huihui-Qwen3.8-27B-abliterated↓ 40,116 this lineage

nchapman/Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ

Metadata

License

apache-2.0

Files by quantization

Auxiliary files 13 files 18.1 GB

model.safetensors	17.3 GB	affa9bb7	download
model_mtp.safetensors	810 MB	1d8268aa	download
tokenizer.json	19.1 MB	67d81139	download
model.safetensors.index.json	164 KB	35296fa8	download
chat_template.jinja	27.6 KB	570ed079	download
config.json	15.0 KB	5ed7fb0c	download
.gitattributes	1.53 KB	52373fe2	download
README.md	1.51 KB	201e2502	download
tokenizer_config.json	1.47 KB	a60ae1a9	download
processor_config.json	1.19 KB	43c4343e	download
SHA256SUMS	855 B	8ba88a28	download
recipe.yaml	386 B	9d1ee00f	download
generation_config.json	177 B	e9c58bd0	download

README current version from Hugging Face

base_model: huihui-ai/Huihui-Qwen3.8-27B-abliterated
license: apache-2.0
library_name: transformers
quantized_by: nchapman
tags:

gptq
w4a16
compressed-tensors
vllm

Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ

INT4 (W4A16) GPTQ quantization of huihui-ai/Huihui-Qwen3.8-27B-abliterated — the same
model at roughly a quarter of the memory, built for vLLM.

Base model: huihui-ai/Huihui-Qwen3.8-27B-abliterated
Calibration data: 999 samples at the dataset's own
proportions from nvidia/Nemotron-Cascade-2-SFT-Data; the
exact rows are pinned in
warp-3090-quant-lab-frozen-data
Chat template: froggeric Qwen-Fixed-Chat-Templates (v22.5)
ships as chat_template.jinja — the artifact's only template
Default sampling (generation_config.json): temperature 1.0, top_p 0.95, top_k 20 — the thinking-mode
defaults of the base model's card; send your own values to override
Recipe and tooling: warp-3090-model-lab

Vision tower, MTP head, linear-attention projections, and lm_head stay BF16.

from vllm import LLM
llm = LLM(model="nchapman/Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ")

nchapman/Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ

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Direct removal

Difference-of-means

Genealogy 0 direct forks

Metadata

Related

Files by quantization

README current version from Hugging Face

Huihui-Qwen3.8-27B-abliterated-W4A16-GPTQ

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