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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:
| 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.).
Quantizations
For the K-quants below, small SSM tensors are kept at higher precision where useful.
-Q6_K quants keep ssm_alpha, ssm_beta, and ssm_out as Q8_0.
-Q5_K and Q4_K quants keep ssm_alpha, ssm_beta as Q8_0 and and ssm_out as Q6_K.
This helps preserve the hybrid/SSM blocks with a small file-size increase.
| Filename | Quant | Description |
|---|
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-BF16.gguf | BF16 | Full precision |
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-Q8_0.gguf | Q8_0 | Near-lossless, recommended |
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-Q6_K.gguf | Q6_K | Excellent quality |
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-Q5_K_M.gguf | Q5_K_M | Good balance |
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-Q5_K_S.gguf | Q5_K_S | Smaller Q5 |
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-Q4_K_M.gguf | Q4_K_M | Good for limited VRAM |
Vision Projector
| Filename | Quant | Description |
|---|
| Qwen3.5-9B-Nikusui-v1-Uncensored-Heretic-Native-MTP-Preserved-mmproj-BF16.gguf | BF16 | Native precision |
A Vision Projector File is Required for vision/multimodal capabilities. Use alongside any quantization above.
Usage
Works with llama.cpp, LM Studio, Ollama, and other GGUF-compatible tools.
Nikusui - v1
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.
