← back to catalog · registered 2026-08-22 13:56

llmfan46/Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved

llmfan46 Qwen 9.7B
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/llmfan46%2FQwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved"
Response includes
  • classification m3
  • files 14
  • hub_downloads_all_time 223
  • author_summary 211 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M3
Primary method

Layer-wise ablation

Applied on top of direct removal inherited from the base model.
Confidence
HIGH
Inherited from base model
Why this label 2 signals
Producer identity confirmed by naming conventions, tags or the model card. This label is very unlikely to change.
  • 'heretic' in model name (Heretic-produced)
  • Heretic uses layer-wise optimization (M3) with underlying direction removal (M1)
Refusal direction extracted via
Extraction technique

Difference-of-means

Confidence
HIGH
Why we say so
name contains 'heretic'; Heretic default extraction is difference-of-means (Arditi 2024)
Downloads · lifetime
223
50 last 30d - stable
Likes
3
Descendants
4
in 4 direct forks
Model age
2mo ago
created 2026-07-30
Downloads over time
Now248→from56↑343%
4612019426756 on Jul 29248 on Oct 11JulAugSepOct
Jul 29 → Oct 11 · 51 snapshots · spans 74 days

Genealogy 4 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.

Variants by this author 2 formats · 2K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
apache-2.0
Tags
safetensors qwen3_5 JLENS Jacobian-Lens uncensored manual-abliteration conversational experimental NSFW very_very_naughty j-wash heretic

Related

Total size
18.0 GB
Files
14
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-07-31 01:33

Files by quantization

Auxiliary files 14 files 18.0 GB
model-00002-of-00004.safetensors 4.65 GB 75ae42a6 download
model-00003-of-00004.safetensors 4.61 GB 14582649 download
model-00001-of-00004.safetensors 4.60 GB afaae9f5 download
model-00004-of-00004.safetensors 3.66 GB 87592dc6 download
model-auxiliary.safetensors 464 MB 30fefebb download
tokenizer.json 19.1 MB 06b95093 download
model.safetensors.index.json 69.4 KB 5abcb0f1 download
README.md 9.46 KB 07bc16f0 download
chat_template.jinja 7.72 KB 945efe1d download
config.json 2.87 KB ba96c50f download
.gitattributes 1.53 KB 52373fe2 download
processor_config.json 1.22 KB 091883f4 download
tokenizer_config.json 1.17 KB 76e376ed download
generation_config.json 122 B a0bd3fc3 download

README current version from Hugging Face


license: apache-2.0
base_model:

  • extraltodeus/Qwen3.5-9B-Nikusui-v1
    tags:
  • JLENS
  • Jacobian-Lens
  • uncensored
  • manual-abliteration
  • conversational
  • qwen3_5
  • experimental
  • NSFW
  • very_very_naughty
  • j-wash
  • heretic
  • uncensored
  • decensored
  • abliterated

🚨⚠️ I HAVE REACHED HUGGING FACE'S FREE STORAGE LIMIT ⚠️🚨

I can no longer upload new models unless I can cover the cost of additional storage.
I host 70+ free models as an independent contributor and this work is unpaid.
Without your support, no more new models can be uploaded.

☕ Ko-fi

Every contribution goes directly toward Hugging Face storage fees to keep models free for everyone.


86% fewer refusals (11/100 Uncensored vs 96/100 Original) while preserving model quality (0.0067 KL divergence).

❤️ Support My Work

Creating these models takes significant time, work and compute. If you find them useful consider supporting me:

image/png

Platform Link What you get
☕ Ko-fi Coffee Tips My eternal gratitude

Your help will motivate me and would go into further improving my workflow and coverings fees for storage, compute and may even help uncensoring bigger model with rental Cloud GPUs.


This is a decensored version of extraltodeus/Qwen3.5-9B-Nikusui-v1, made using Heretic v1.4.0 with a variant of the Magnitude-Preserving Orthogonal Ablation (MPOA) method

Abliteration parameters

Parameter Value
direction_index 21.14
attn.out_proj.max_weight 1.90
attn.out_proj.max_weight_position 20.21
attn.out_proj.min_weight 1.38
attn.out_proj.min_weight_distance 20.35
mlp.down_proj.max_weight 1.96
mlp.down_proj.max_weight_position 19.78
mlp.down_proj.min_weight 1.22
mlp.down_proj.min_weight_distance 12.52
attn.o_proj.max_weight 1.83
attn.o_proj.max_weight_position 19.22
attn.o_proj.min_weight 0.47
attn.o_proj.min_weight_distance 23.77

Targeted components

  • attn.out_proj
  • mlp.down_proj
  • attn.o_proj

Performance

Metric This model Original model (Qwen3.5-9B-Nikusui-v1)
KL divergence 0.0067 0 (by definition)
Refusals ✅ 11/100 ❌ 96/100

MMLU test results:

Original:

============================================================

  • Total questions: 7021

  • Correct: 5426

  • Accuracy: 0.7728 (77.28%)

  • Parse failures: 0

============================================================

Tested subject scores:

  • professional_law: 0.6140 (482/785)
  • moral_scenarios: 0.4796 (212/442)
  • miscellaneous: 0.8825 (338/383)
  • professional_psychology: 0.8259 (261/316)
  • high_school_psychology: 0.9519 (257/270)
  • high_school_macroeconomics: 0.8426 (166/197)
  • elementary_mathematics: 0.7011 (129/184)
  • moral_disputes: 0.7989 (139/174)
  • prehistory: 0.8547 (147/172)
  • philosophy: 0.7862 (125/159)
  • high_school_biology: 0.9539 (145/152)
  • professional_accounting: 0.6573 (94/143)
  • clinical_knowledge: 0.8143 (114/140)
  • high_school_microeconomics: 0.9338 (127/136)
  • nutrition: 0.8296 (112/135)
  • professional_medicine: 0.8731 (117/134)
  • conceptual_physics: 0.8359 (107/128)
  • high_school_mathematics: 0.5433 (69/127)
  • human_aging: 0.7759 (90/116)
  • security_studies: 0.8750 (98/112)
  • high_school_statistics: 0.7568 (84/111)
  • marketing: 0.9450 (103/109)
  • high_school_world_history: 0.9245 (98/106)
  • sociology: 0.9126 (94/103)
  • high_school_government_and_politics: 0.9604 (97/101)
  • high_school_geography: 0.9293 (92/99)
  • high_school_chemistry: 0.7629 (74/97)
  • high_school_us_history: 0.9368 (89/95)
  • virology: 0.5169 (46/89)
  • college_medicine: 0.7955 (70/88)
  • world_religions: 0.8750 (77/88)
  • high_school_physics: 0.6548 (55/84)
  • electrical_engineering: 0.7160 (58/81)
  • astronomy: 0.9241 (73/79)
  • logical_fallacies: 0.8289 (63/76)
  • high_school_european_history: 0.8767 (64/73)
  • anatomy: 0.8028 (57/71)
  • college_biology: 0.9219 (59/64)
  • human_sexuality: 0.8125 (52/64)
  • formal_logic: 0.6406 (41/64)
  • public_relations: 0.7377 (45/61)
  • international_law: 0.9000 (54/60)
  • college_physics: 0.6316 (36/57)
  • college_mathematics: 0.5455 (30/55)
  • econometrics: 0.7037 (38/54)
  • jurisprudence: 0.8679 (46/53)
  • high_school_computer_science: 0.8269 (43/52)
  • machine_learning: 0.6346 (33/52)
  • medical_genetics: 0.9020 (46/51)
  • global_facts: 0.4510 (23/51)
  • management: 0.9400 (47/50)
  • us_foreign_policy: 0.9400 (47/50)
  • college_chemistry: 0.5532 (26/47)
  • abstract_algebra: 0.6383 (30/47)
  • business_ethics: 0.6957 (32/46)
  • college_computer_science: 0.8444 (38/45)
  • computer_security: 0.8605 (37/43)

Heretic:

============================================================

  • Total questions: 7021

  • Correct: 5413

  • Accuracy: 0.7710 (77.10%)

  • Parse failures: 0

============================================================

Tested subject scores:

  • professional_law: 0.6089 (478/785)
  • moral_scenarios: 0.4774 (211/442)
  • miscellaneous: 0.8877 (340/383)
  • professional_psychology: 0.8291 (262/316)
  • high_school_psychology: 0.9519 (257/270)
  • high_school_macroeconomics: 0.8528 (168/197)
  • elementary_mathematics: 0.7011 (129/184)
  • moral_disputes: 0.7989 (139/174)
  • prehistory: 0.8488 (146/172)
  • philosophy: 0.7673 (122/159)
  • high_school_biology: 0.9539 (145/152)
  • professional_accounting: 0.6573 (94/143)
  • clinical_knowledge: 0.8143 (114/140)
  • high_school_microeconomics: 0.9338 (127/136)
  • nutrition: 0.8370 (113/135)
  • professional_medicine: 0.8582 (115/134)
  • conceptual_physics: 0.8359 (107/128)
  • high_school_mathematics: 0.5512 (70/127)
  • human_aging: 0.7759 (90/116)
  • security_studies: 0.8571 (96/112)
  • high_school_statistics: 0.7387 (82/111)
  • marketing: 0.9450 (103/109)
  • high_school_world_history: 0.9151 (97/106)
  • sociology: 0.9223 (95/103)
  • high_school_government_and_politics: 0.9505 (96/101)
  • high_school_geography: 0.9394 (93/99)
  • high_school_chemistry: 0.7629 (74/97)
  • high_school_us_history: 0.9368 (89/95)
  • virology: 0.5169 (46/89)
  • college_medicine: 0.8068 (71/88)
  • world_religions: 0.8864 (78/88)
  • high_school_physics: 0.6548 (55/84)
  • electrical_engineering: 0.7160 (58/81)
  • astronomy: 0.9241 (73/79)
  • logical_fallacies: 0.8421 (64/76)
  • high_school_european_history: 0.8767 (64/73)
  • anatomy: 0.8028 (57/71)
  • college_biology: 0.9375 (60/64)
  • human_sexuality: 0.8125 (52/64)
  • formal_logic: 0.6250 (40/64)
  • public_relations: 0.7049 (43/61)
  • international_law: 0.8667 (52/60)
  • college_physics: 0.6316 (36/57)
  • college_mathematics: 0.5455 (30/55)
  • econometrics: 0.6667 (36/54)
  • jurisprudence: 0.8679 (46/53)
  • high_school_computer_science: 0.8269 (43/52)
  • machine_learning: 0.6346 (33/52)
  • medical_genetics: 0.8824 (45/51)
  • global_facts: 0.4314 (22/51)
  • management: 0.9400 (47/50)
  • us_foreign_policy: 0.9600 (48/50)
  • college_chemistry: 0.5319 (25/47)
  • abstract_algebra: 0.6596 (31/47)
  • business_ethics: 0.6957 (32/46)
  • college_computer_science: 0.8444 (38/45)
  • computer_security: 0.8372 (36/43)

MMLU - Massive Multitask Language Understanding, multiple-choice questions across 57 subjects (math, history, law, medicine, etc.).

GGUF Version

GGUF quantizations available here llmfan46/Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-GGUF.


Nikusui - v1

nikusui2

Nikusui is a manually abliterated Qwen3.5-9B-Base model using a custom tool in the making and based on Anthropic's Jacobian-Lens.

The tool is currently still a work in progress but I intend to share it. I just need to sleep after spend three days on this. 😴

It will allow to save a model while retaining the effects of any modification made in the J-Space. Suppression and replacement.

Nikusui-v1 is the very first created by this tool and is a fully working proof of concept.

I haven't decided a name for the tool yet 🤭 J-Wash it is!

If you're curious : the file "edit_meta.json" contains the settings I used in my tool to edit the base model and will give you more clues about why it behaves like it does.

All modifications were made on Qwen/Qwen3.5-9B-Base directly.

THIS MODEL WILL SPONTANEOUSLY PRODUCE HARMFUL CONTENT ! Or at least offer a spanking.

In the name of science.

README history 2 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-07-31Update README.md61465bc9.5 KB
    Loading...
  2. 2026-07-30Upload folder using huggingface_hub7e279b79.4 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration