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llmfan46/Forgotten-Transgression-24B-v4.1-uncensored-heretic

llmfan46 Mistral 24B
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  • files 8
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  • author_summary 211 models
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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
120
18 last 30d - stable
Likes
1
Descendants
3
in 3 direct forks
Model age
6mo ago
created 2026-04-01
Downloads over time
Now125→from80↑56%
789511213080 on Apr 15125 on Oct 11125 on Oct 9AprMayJunJulAugSepOct
Apr 15 → Oct 11 · 65 snapshots · spans 179 days

Genealogy 3 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 · 158 downloads combined

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

Metadata

License
apache-2.0
Languages
en
Tags
safetensors mistral nsfw explicit roleplay unaligned dangerous ERP heretic uncensored decensored abliterated

Related

Total size
43.9 GB
Files
8
Quantizations
1
Registered
2026-08-22 13:56
Last updated on HF
2026-04-03 01:23

Files by quantization

Auxiliary files 8 files 43.9 GB
model.safetensors 43.9 GB 2f72e6f9 download
tokenizer.json 16.3 MB 5bc988cc download
README.md 24.4 KB 700ede6f download
chat_template.jinja 1.58 KB 2d0058c5 download
.gitattributes 1.53 KB 52373fe2 download
config.json 832 B f1a7b5f8 download
tokenizer_config.json 352 B 3144b8ce download
generation_config.json 225 B 5ca5d869 download

README current version from Hugging Face


base_model:

  • ReadyArt/Forgotten-Transgression-24B-v4.1
    base_model_relation: finetune
    language:
  • en
    license: apache-2.0
    inference: false
    tags:
  • nsfw
  • explicit
  • roleplay
  • unaligned
  • dangerous
  • ERP
  • heretic
  • uncensored
  • decensored
  • abliterated
  • ara

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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.

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94% fewer refusals (6/100 Uncensored vs 95/100 Original) while preserving model quality (0.0232 KL divergence).

❤️ Support My Work

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

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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.


This is a decensored version of ReadyArt/Forgotten-Transgression-24B-v4.1, made using Heretic v1.2.0 with the Arbitrary-Rank Ablation (ARA) method

Abliteration parameters

Parameter Value
start_layer_index 15
end_layer_index 32
preserve_good_behavior_weight 0.8783
steer_bad_behavior_weight 0.0001
overcorrect_relative_weight 0.9058
neighbor_count 2

Targeted components

  • attn.o_proj

Performance

Metric This model Original model (Forgotten-Transgression-24B-v4.1)
KL divergence 0.0232 0 (by definition)
Refusals ✅ 6/100 ❌ 95/100

PIQA test results with batch size 128:

Original:

Tasks Version Filter n-shot Metric Value Stderr
piqa 1 none 0 acc ↑ 0.8237 ± 0.0089
none 0 acc_norm ↑ 0.8351 ± 0.0087

Heretic:

Tasks Version Filter n-shot Metric Value Stderr
piqa 1 none 0 acc ↑ 0.8237 ± 0.0089
none 0 acc_norm ↑ 0.8373 ± 0.0086

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. PIQA (Physical Intuition Question Answering) a ~1,800 questions tests common-sense understanding of how the physical world works with benchmark scores to measure physical reasoning ability. The Heretic model's acc and acc_norm scores closer to the original model's indicate better capability preservation, a big decrease in acc and acc_norm in the Heretic model compared to Original model's results means a big decrease in the Hereticated model capabilities. acc measures raw accuracy (which answer gets higher probability), while acc_norm measures length-normalized accuracy (corrects for answer length bias). For this purpose, acc_norm matters more because longer answers naturally have lower probabilities (more tokens = more chances to lose probability). Without normalization, models favor shorter answers unfairly. acc_norm divides by answer length to correct this.

MMLU test results with batch size 32:

Original:

Tasks Version Filter n-shot Metric Value Stderr
mmlu 2 none acc ↑ 0.7896 ± 0.0033
- humanities 2 none acc ↑ 0.7239 ± 0.0062
- formal_logic 1 none 0 acc ↑ 0.5556 ± 0.0444
- high_school_european_history 1 none 0 acc ↑ 0.8545 ± 0.0275
- high_school_us_history 1 none 0 acc ↑ 0.9069 ± 0.0204
- high_school_world_history 1 none 0 acc ↑ 0.9072 ± 0.0189
- international_law 1 none 0 acc ↑ 0.9008 ± 0.0273
- jurisprudence 1 none 0 acc ↑ 0.8519 ± 0.0343
- logical_fallacies 1 none 0 acc ↑ 0.8712 ± 0.0263
- moral_disputes 1 none 0 acc ↑ 0.8266 ± 0.0204
- moral_scenarios 1 none 0 acc ↑ 0.6123 ± 0.0163
- philosophy 1 none 0 acc ↑ 0.8199 ± 0.0218
- prehistory 1 none 0 acc ↑ 0.8704 ± 0.0187
- professional_law 1 none 0 acc ↑ 0.6056 ± 0.0125
- world_religions 1 none 0 acc ↑ 0.8889 ± 0.0241
- other 2 none acc ↑ 0.8313 ± 0.0064
- business_ethics 1 none 0 acc ↑ 0.7900 ± 0.0409
- clinical_knowledge 1 none 0 acc ↑ 0.8566 ± 0.0216
- college_medicine 1 none 0 acc ↑ 0.7746 ± 0.0319
- global_facts 1 none 0 acc ↑ 0.5700 ± 0.0498
- human_aging 1 none 0 acc ↑ 0.7982 ± 0.0269
- management 1 none 0 acc ↑ 0.9029 ± 0.0293
- marketing 1 none 0 acc ↑ 0.9316 ± 0.0165
- medical_genetics 1 none 0 acc ↑ 0.9000 ± 0.0302
- miscellaneous 1 none 0 acc ↑ 0.9170 ± 0.0099
- nutrition 1 none 0 acc ↑ 0.8856 ± 0.0182
- professional_accounting 1 none 0 acc ↑ 0.6667 ± 0.0281
- professional_medicine 1 none 0 acc ↑ 0.8750 ± 0.0201
- virology 1 none 0 acc ↑ 0.5542 ± 0.0387
- social sciences 2 none acc ↑ 0.8772 ± 0.0058
- econometrics 1 none 0 acc ↑ 0.7018 ± 0.0430
- high_school_geography 1 none 0 acc ↑ 0.9091 ± 0.0205
- high_school_government_and_politics 1 none 0 acc ↑ 0.9689 ± 0.0125
- high_school_macroeconomics 1 none 0 acc ↑ 0.8359 ± 0.0188
- high_school_microeconomics 1 none 0 acc ↑ 0.9160 ± 0.0180
- high_school_psychology 1 none 0 acc ↑ 0.9303 ± 0.0109
- human_sexuality 1 none 0 acc ↑ 0.8779 ± 0.0287
- professional_psychology 1 none 0 acc ↑ 0.8595 ± 0.0141
- public_relations 1 none 0 acc ↑ 0.7818 ± 0.0396
- security_studies 1 none 0 acc ↑ 0.8286 ± 0.0241
- sociology 1 none 0 acc ↑ 0.8905 ± 0.0221
- us_foreign_policy 1 none 0 acc ↑ 0.9200 ± 0.0273
- stem 2 none acc ↑ 0.7612 ± 0.0073
- abstract_algebra 1 none 0 acc ↑ 0.5800 ± 0.0496
- anatomy 1 none 0 acc ↑ 0.7630 ± 0.0367
- astronomy 1 none 0 acc ↑ 0.9211 ± 0.0219
- college_biology 1 none 0 acc ↑ 0.9444 ± 0.0192
- college_chemistry 1 none 0 acc ↑ 0.5100 ± 0.0502
- college_computer_science 1 none 0 acc ↑ 0.7200 ± 0.0451
- college_mathematics 1 none 0 acc ↑ 0.5600 ± 0.0499
- college_physics 1 none 0 acc ↑ 0.6275 ± 0.0481
- computer_security 1 none 0 acc ↑ 0.8100 ± 0.0394
- conceptual_physics 1 none 0 acc ↑ 0.8383 ± 0.0241
- electrical_engineering 1 none 0 acc ↑ 0.8000 ± 0.0333
- elementary_mathematics 1 none 0 acc ↑ 0.7963 ± 0.0207
- high_school_biology 1 none 0 acc ↑ 0.9226 ± 0.0152
- high_school_chemistry 1 none 0 acc ↑ 0.7783 ± 0.0292
- high_school_computer_science 1 none 0 acc ↑ 0.9100 ± 0.0288
- high_school_mathematics 1 none 0 acc ↑ 0.5667 ± 0.0302
- high_school_physics 1 none 0 acc ↑ 0.6291 ± 0.0394
- high_school_statistics 1 none 0 acc ↑ 0.7639 ± 0.0290
- machine_learning 1 none 0 acc ↑ 0.6875 ± 0.0440
Groups Version Filter n-shot Metric Value Stderr
mmlu 2 none acc ↑ 0.7896 ± 0.0033
- humanities 2 none acc ↑ 0.7239 ± 0.0062
- other 2 none acc ↑ 0.8313 ± 0.0064
- social sciences 2 none acc ↑ 0.8772 ± 0.0058
- stem 2 none acc ↑ 0.7612 ± 0.0073

Heretic:

Tasks Version Filter n-shot Metric Value Stderr
mmlu 2 none acc ↑ 0.7879 ± 0.0033
- humanities 2 none acc ↑ 0.7211 ± 0.0063
- formal_logic 1 none 0 acc ↑ 0.5873 ± 0.0440
- high_school_european_history 1 none 0 acc ↑ 0.8545 ± 0.0275
- high_school_us_history 1 none 0 acc ↑ 0.9069 ± 0.0204
- high_school_world_history 1 none 0 acc ↑ 0.9198 ± 0.0177
- international_law 1 none 0 acc ↑ 0.8760 ± 0.0301
- jurisprudence 1 none 0 acc ↑ 0.8426 ± 0.0352
- logical_fallacies 1 none 0 acc ↑ 0.8650 ± 0.0268
- moral_disputes 1 none 0 acc ↑ 0.8179 ± 0.0208
- moral_scenarios 1 none 0 acc ↑ 0.5989 ± 0.0164
- philosophy 1 none 0 acc ↑ 0.8232 ± 0.0217
- prehistory 1 none 0 acc ↑ 0.8765 ± 0.0183
- professional_law 1 none 0 acc ↑ 0.6037 ± 0.0125
- world_religions 1 none 0 acc ↑ 0.8889 ± 0.0241
- other 2 none acc ↑ 0.8301 ± 0.0064
- business_ethics 1 none 0 acc ↑ 0.8100 ± 0.0394
- clinical_knowledge 1 none 0 acc ↑ 0.8604 ± 0.0213
- college_medicine 1 none 0 acc ↑ 0.7746 ± 0.0319
- global_facts 1 none 0 acc ↑ 0.5700 ± 0.0498
- human_aging 1 none 0 acc ↑ 0.8072 ± 0.0265
- management 1 none 0 acc ↑ 0.9126 ± 0.0280
- marketing 1 none 0 acc ↑ 0.9274 ± 0.0170
- medical_genetics 1 none 0 acc ↑ 0.9100 ± 0.0288
- miscellaneous 1 none 0 acc ↑ 0.9157 ± 0.0099
- nutrition 1 none 0 acc ↑ 0.8856 ± 0.0182
- professional_accounting 1 none 0 acc ↑ 0.6560 ± 0.0283
- professional_medicine 1 none 0 acc ↑ 0.8603 ± 0.0211
- virology 1 none 0 acc ↑ 0.5422 ± 0.0388
- social sciences 2 none acc ↑ 0.8749 ± 0.0059
- econometrics 1 none 0 acc ↑ 0.6842 ± 0.0437
- high_school_geography 1 none 0 acc ↑ 0.9091 ± 0.0205
- high_school_government_and_politics 1 none 0 acc ↑ 0.9741 ± 0.0115
- high_school_macroeconomics 1 none 0 acc ↑ 0.8231 ± 0.0193
- high_school_microeconomics 1 none 0 acc ↑ 0.9034 ± 0.0192
- high_school_psychology 1 none 0 acc ↑ 0.9321 ± 0.0108
- human_sexuality 1 none 0 acc ↑ 0.8779 ± 0.0287
- professional_psychology 1 none 0 acc ↑ 0.8660 ± 0.0138
- public_relations 1 none 0 acc ↑ 0.7818 ± 0.0396
- security_studies 1 none 0 acc ↑ 0.8082 ± 0.0252
- sociology 1 none 0 acc ↑ 0.9005 ± 0.0212
- us_foreign_policy 1 none 0 acc ↑ 0.9200 ± 0.0273
- stem 2 none acc ↑ 0.7612 ± 0.0073
- abstract_algebra 1 none 0 acc ↑ 0.6100 ± 0.0490
- anatomy 1 none 0 acc ↑ 0.7852 ± 0.0355
- astronomy 1 none 0 acc ↑ 0.9211 ± 0.0219
- college_biology 1 none 0 acc ↑ 0.9444 ± 0.0192
- college_chemistry 1 none 0 acc ↑ 0.5200 ± 0.0502
- college_computer_science 1 none 0 acc ↑ 0.7000 ± 0.0461
- college_mathematics 1 none 0 acc ↑ 0.5700 ± 0.0498
- college_physics 1 none 0 acc ↑ 0.6176 ± 0.0484
- computer_security 1 none 0 acc ↑ 0.8200 ± 0.0386
- conceptual_physics 1 none 0 acc ↑ 0.8298 ± 0.0246
- electrical_engineering 1 none 0 acc ↑ 0.8000 ± 0.0333
- elementary_mathematics 1 none 0 acc ↑ 0.8069 ± 0.0203
- high_school_biology 1 none 0 acc ↑ 0.9258 ± 0.0149
- high_school_chemistry 1 none 0 acc ↑ 0.7734 ± 0.0295
- high_school_computer_science 1 none 0 acc ↑ 0.8900 ± 0.0314
- high_school_mathematics 1 none 0 acc ↑ 0.5593 ± 0.0303
- high_school_physics 1 none 0 acc ↑ 0.6291 ± 0.0394
- high_school_statistics 1 none 0 acc ↑ 0.7546 ± 0.0293
- machine_learning 1 none 0 acc ↑ 0.6696 ± 0.0446
Groups Version Filter n-shot Metric Value Stderr
mmlu 2 none acc ↑ 0.7879 ± 0.0033
- humanities 2 none acc ↑ 0.7211 ± 0.0063
- other 2 none acc ↑ 0.8301 ± 0.0064
- social sciences 2 none acc ↑ 0.8749 ± 0.0059
- stem 2 none acc ↑ 0.7612 ± 0.0073

MMLU - Massive Multitask Language Understanding, ~14,000 multiple-choice questions across 57 subjects (math, history, law, medicine, etc.).

GGUF Version

GGUF quantizations available here llmfan46/Forgotten-Transgression-24B-v4.1-uncensored-heretic-GGUF.


Forgotten-Transgression-24B-v4.1

Crossing the Event Horizon of Depravity
Protocol Mascot

📜 Manifesto

  • 🔁 Finetuned for unprecedented coherent depravity up to 32K context
  • 🛠️ Optimized for stability and well-rounded erotic roleplaying ability
  • 💥 Trained on 23 distinct types of taboo content

⚙️ Technical Specifications

Recommended Settings: Mistral-V7-Tekken-T

⚠️ Ethical Considerations

This model will:

  • Generate content that requires industrial-grade brain bleach
  • Void all warranties on your soul
  • Make you question why humanity ever invented electricity

📜 License Agreement

By using this model, you agree:

  • To accept full responsibility for any psychotic breaks incurred
  • Pay for the exorcist of anyone who reads the logs
  • To pretend this is "for science" while crying in the shower

🧠 Model Author

  • sleepdeprived3 (Chief Corruption Officer)

☕️ Drummer made this possible

README history 6 versions

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

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