llmfan46
Gemma-4-Harmonia-31B-it-uncensored-heretic Available on FriendliAI
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Model Tree
Base
ConicCat/Gemma4-GarnetV2-31B
Base
LatitudeGames/Equinox-31B
Base
llmfan46/G4-MeroMero-31B-uncensored-heretic
Base
llmfan46/gemma-4-Ortenzya-The-Creative-Wordsmith-31B-it-uncensored-heretic
Base
Lambent/Fabled-Gemma4-31B
Base
google/gemma-4-31B-it
Base
llmfan46/Gemma-4-Gembrain-31B-it-uncensored-heretic
Input Modalities
Text Image
Supported Functionality
Dedicated Endpoints
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Gemma-4-Harmonia-31B-it-uncensored-heretic API & Inference Endpoint | FriendliAI
README ❤️ Support My Work
Creating these models takes significant time, work and compute. If you find them useful consider supporting me:
Table with columns: Platform, Link, What you get Platform Link What you get 🎉 Patreon Monthly support Priority model requests ☕ Ko-fi One-time tip 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.
Abliteration parameters
Table with columns: Parameter, Value Parameter Value start_layer_index 14 end_layer_index 55 preserve_good_behavior_weight 0.7754 steer_bad_behavior_weight 0.0001 overcorrect_relative_weight 0.9765 neighbor_count 14
Targeted components
Table with columns: Metric, This model, Original model (Gemma-4-Harmonia-31B) Metric This model Original model (Gemma-4-Harmonia-31B ) KL divergence 0.0047 0 (by definition) Refusals ✅ 9/100 ❌ 97/100
Lower refusals indicate fewer content restrictions, while lower KL divergence indicates more closeness to the original model's baseline. Higher refusals cause more rejections, objections, pushbacks, lecturing, censorship, softening and deflections.
MMLU test results:
Original:
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Tested subject scores:
professional_law: 0.7592 (596/785)
moral_scenarios: 0.8394 (371/442)
miscellaneous: 0.9243 (354/383)
professional_psychology: 0.8797 (278/316)
high_school_psychology: 0.9593 (259/270)
high_school_macroeconomics: 0.9137 (180/197)
elementary_mathematics: 0.9239 (170/184)
moral_disputes: 0.8678 (151/174)
prehistory: 0.9128 (157/172)
philosophy: 0.8553 (136/159)
high_school_biology: 0.9605 (146/152)
professional_accounting: 0.7902 (113/143)
clinical_knowledge: 0.8929 (125/140)
high_school_microeconomics: 0.9632 (131/136)
nutrition: 0.8815 (119/135)
professional_medicine: 0.9104 (122/134)
Heretic:
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Tested subject scores:
professional_law: 0.7121 (559/785)
moral_scenarios: 0.8281 (366/442)
miscellaneous: 0.9191 (352/383)
professional_psychology: 0.8703 (275/316)
high_school_psychology: 0.9593 (259/270)
high_school_macroeconomics: 0.9188 (181/197)
elementary_mathematics: 0.9348 (172/184)
moral_disputes: 0.8448 (147/174)
prehistory: 0.9128 (157/172)
philosophy: 0.8113 (129/159)
high_school_biology: 0.9605 (146/152)
professional_accounting: 0.7902 (113/143)
clinical_knowledge: 0.8786 (123/140)
high_school_microeconomics: 0.9559 (130/136)
nutrition: 0.8815 (119/135)
professional_medicine: 0.9030 (121/134)
MMLU - Massive Multitask Language Understanding, multiple-choice questions across 57 subjects (math, history, law, medicine, etc.).
GGUF Version
GGUF quantizations available here llmfan46/Gemma-4-Harmonia-31B-it-uncensored-heretic-GGUF .
Harmonious Synthesis
Multi-Stage Fusion Protocol
Methodological Innovations
Model Lineage & Ingredients
Merge Blueprint
name : clever - basename
merge_method : nullspace
base_model : ./gemma - 4 - 31B - base
models :
- model : ./Gemma4 - GarnetV2 - 31B
parameters :
weight : 1.0
parameters :
protect_base : true
nr : 256
tokenizer :
source : base
chat_template : auto
dtype : float32
out_dtype : bfloat16
---
name : clever - intname
merge_method : cabs
base_model : ./clever - basename
models :
- model : ./clever - basename
- model : ./G4 - MeroMero - 31B - uncensored - heretic
parameters :
weight : 0.6
n_val : 16
m_val : 32
- model : ./Gemma - 4 - Gembrain - 31B - heretic
parameters :
weight : 0.4
n_val : 11
m_val : 33
default_n_val : 8
default_m_val : 32
pruning_order :
- ./G4 - MeroMero - 31B - uncensored - heretic
- ./Gemma - 4 - Gembrain - 31B - heretic
dtype : float32
out_dtype : bfloat16
tokenizer :
source : union
chat_template : auto
---
name : Harmonia
merge_method : actmat
base_model : ./gemma - 4 - Ortenzya - The - Creative - Wordsmith - 31B - it - uncensored - heretic
models :
- model : ./gemma - 4 - Ortenzya - The - Creative - Wordsmith - 31B - it - uncensored - heretic
- model : ./LatitudeGames - Equinox - 31B
parameters :
weight : 1
- model : ./clever - intname
parameters :
weight : 1
- model : ./Fabled - Gemma4 - 31B
parameters :
weight : 1
parameters :
epsilon : 1e-6
tokenizer :
source : "union"
dtype : bfloat16
out_dtype : bfloat16
chat_template : auto
Symphony Contributors
conceptual_physics: 0.9062 (116/128)
high_school_mathematics: 0.5669 (72/127)
human_aging: 0.8448 (98/116)
security_studies: 0.8571 (96/112)
high_school_statistics: 0.8649 (96/111)
marketing: 0.9725 (106/109)
high_school_world_history: 0.9528 (101/106)
sociology: 0.9223 (95/103)
high_school_government_and_politics: 0.9406 (95/101)
high_school_geography: 0.9596 (95/99)
high_school_chemistry: 0.7835 (76/97)
high_school_us_history: 0.9053 (86/95)
virology: 0.5056 (45/89)
college_medicine: 0.8636 (76/88)
world_religions: 0.9205 (81/88)
high_school_physics: 0.7619 (64/84)
electrical_engineering: 0.8395 (68/81)
astronomy: 0.9241 (73/79)
logical_fallacies: 0.8816 (67/76)
high_school_european_history: 0.8904 (65/73)
anatomy: 0.8732 (62/71)
college_biology: 0.9844 (63/64)
human_sexuality: 0.8750 (56/64)
formal_logic: 0.7031 (45/64)
public_relations: 0.7213 (44/61)
international_law: 0.8667 (52/60)
college_physics: 0.7193 (41/57)
college_mathematics: 0.7818 (43/55)
econometrics: 0.7407 (40/54)
jurisprudence: 0.8302 (44/53)
high_school_computer_science: 0.9808 (51/52)
machine_learning: 0.8462 (44/52)
medical_genetics: 0.9020 (46/51)
global_facts: 0.5686 (29/51)
management: 0.8800 (44/50)
us_foreign_policy: 0.9800 (49/50)
college_chemistry: 0.6170 (29/47)
abstract_algebra: 0.7447 (35/47)
business_ethics: 0.8478 (39/46)
college_computer_science: 0.9333 (42/45)
computer_security: 0.8605 (37/43)
conceptual_physics: 0.8828 (113/128)
high_school_mathematics: 0.5433 (69/127)
human_aging: 0.8448 (98/116)
security_studies: 0.8571 (96/112)
high_school_statistics: 0.8559 (95/111)
marketing: 0.9817 (107/109)
high_school_world_history: 0.9528 (101/106)
sociology: 0.9223 (95/103)
high_school_government_and_politics: 0.9406 (95/101)
high_school_geography: 0.9596 (95/99)
high_school_chemistry: 0.7835 (76/97)
high_school_us_history: 0.8947 (85/95)
virology: 0.5056 (45/89)
college_medicine: 0.8295 (73/88)
world_religions: 0.9205 (81/88)
high_school_physics: 0.7619 (64/84)
electrical_engineering: 0.8148 (66/81)
astronomy: 0.9367 (74/79)
logical_fallacies: 0.8947 (68/76)
high_school_european_history: 0.8630 (63/73)
anatomy: 0.8873 (63/71)
college_biology: 0.9844 (63/64)
human_sexuality: 0.8750 (56/64)
formal_logic: 0.7031 (45/64)
public_relations: 0.6885 (42/61)
international_law: 0.8667 (52/60)
college_physics: 0.7193 (41/57)
college_mathematics: 0.7455 (41/55)
econometrics: 0.7407 (40/54)
jurisprudence: 0.8113 (43/53)
high_school_computer_science: 0.9808 (51/52)
machine_learning: 0.8077 (42/52)
medical_genetics: 0.9020 (46/51)
global_facts: 0.5686 (29/51)
management: 0.8800 (44/50)
us_foreign_policy: 0.9600 (48/50)
college_chemistry: 0.6383 (30/47)
abstract_algebra: 0.7447 (35/47)
business_ethics: 0.8478 (39/46)
college_computer_science: 0.9333 (42/45)
computer_security: 0.8372 (36/43)
