Silicone-Moss/Darkhn-M3.2-36B-Animus-V12.0-Heretic-Uncensored

Model Summary

Darkhn-M3.2-36B-Animus-V12.0-Heretic-Absolute is a fine-tuned language model resulting from the Heretic repository and optimization methodology, built upon Darkhn's highly capable M3.2-36B-Animus-V12.0 architecture and maintained by the Silicone-Moss repository. It utilizes a targeted vector intervention technique (orthogonalization) tuned via Optuna to suppress refusal responses while maintaining exceptional coherence and probability distribution (KL Divergence).

This specific checkpoint represents Trial 177 KL Divergence of 0.0200. indicating high adherence to the base model's probability distribution. The trade-off is a non-zero refusal rate (8 refusals logged in the test set), making it a highly intelligent but with enough friction to keep the prose high quality.

Run Configuration: "Trial 177"

The following parameters define the intervention vector applied to the model. This configuration was discovered during a deep hyperparameter search, revealing an aggressive scaling strategy on the attention outputs while maintaining a light touch on the MLPs.

Optimization Results

Intervention Parameters

Interventions were applied to two primary distinct layers: the Attention Output Projection (attn.o\proj) and the MLP Down Projection (mlp.down\proj). The data shows Optuna heavily penalizing the attention mechanism deep in the network while barely whispering to the MLP.

Methodology & Definitions

To ensure uniform understanding of the Heretic run data, the following definitions apply to the parameters listed above:

• —Direction Scope: Defines whether the refusal vector is calculated once for the entire model ("Global") or recalculated individually for each layer ("Per Layer"). "Per Layer" allows for precise removal of refusal mechanisms without damaging general knowledge.
• —Max Weight: The maximum scaling factor applied to the intervention vector. A higher weight indicates a stronger "push" against the targeted concept (refusal) at the peak layer. Note the massive 3.4x weight applied to the attention projection in this run.
• —Max Weight Position: The specific layer index (depth) where the intervention is strongest.
• —Observation: The intervention peak sits deep in the model (Layers 35-42), confirming that higher-order reasoning and refusal circuitry coalesce late in the Animus architecture.
• —Min Weight: The baseline scaling factor applied to the intervention vector at the periphery of the target zone.
• —Distance: The "spread" or bandwidth of the intervention. It determines how many layers around the "Max Weight Position" are affected by the vector modification.

Usage & Limitations

• —Intended Use: Research into model alignment, vector arithmetic, and uninhibited creative writing.
• —Risks: As an "Absolute" variant, this model has had most of its safety guardrails stripped via heretic intervention. It may still hallucinate or diverge from logical consistency.

Credits & References

This research builds upon the excellent work of the open-source AI community:

• —Repository / Distribution: Silicone-Moss
• —Base Model: M3.2-36B-Animus-V12.0 by the skilled mind of Darkhn.
• —Methodology: Heretic by p-e-w.

• —Original Model card and support links below

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.format-list dd:last-of-type { margin-bottom: 0; } </style> <div class="container"> <link href="https://fonts.googleapis.com/css2?family=Cinzel:wght@400;500;600&family=Quicksand:wght@400;500&display=swap" rel="stylesheet"> <div class="header"> <h1>M3.2-36B-Animus-V12.0</h1> </div> <div class="support-section"> <p><strong>Send me your support to help me feed the data beast! also taking comissions for universe specific models</strong></p> <a href="https://ko-fi.com/som1tokmynam" target="blank" class="button"> Support on Ko-fi </a> </div> <div class="section-container"> <details open> <summary><h2>Important: Chat Template</h2></summary> <div class="info-card"> <div class="card-content"> <p>This model uses the <strong>Mistral</strong> instruction template. Ensure your client is configured correctly to avoid degraded performance.</p> <p><strong>Human-Readable Format:</strong></p> <p><code>[SYSTEMPROMPT]System Message[/SYSTEMPROMPT][INST]User Message[/INST]Assistant Response</code></p> <p><strong>Jinja Template:</strong></p> <pre><code>{{ bostoken }}{% for message in messages %}{% if message['role'] == 'user' %}{{ '[INST]' + message['content'] + '[/INST]' }}{% elif message['role'] == 'system' %}{{ '[SYSTEMPROMPT]' + message['content'] + '[/SYSTEMPROMPT]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eostoken }}{% else %}{{ raiseexception('Only user, system and assistant roles are supported!') }}{% endif %}{% endfor %}</code></pre> </div> </div> </details> </div> <div class="section-container"> <details> <summary><h2>Quantized Models</h2></summary> <div class="info-card"> <div class="card-content"> <p>The quantized model files are available for download. Click the button below to view the files.</p> <a href="https://huggingface.co/Darkhn-Quants-2/M3.2-36B-Animus-V12.0-GGUF" target="blank" class="button"> Download GGUF Files <span class="link-arrow">→</span> </a> <a href="https://huggingface.co/Darkhn-Quants-2/M3.2-36B-Animus-V12.0-EXL3" target="blank" class="button"> Download EXL3 Files <span class="link-arrow">→</span> </a> </div> </div> </details> </div> <div class="section-container"> <details> <summary><h2>Character Card & Lore Book</h2></summary> <div class="info-card"> <div class="card-content"> <p>For the best roleplaying experience, it is highly recommended to use the provided character card and lore book. These files help guide the model's persona and provide rich, in-universe context.</p> <a href="https://huggingface.co/Darkhn/Samplersettingsandsystemprompt/tree/main/charactercard" target="blank" class="button"> Download Files <span class="link-arrow">→</span> </a> </div> </div> </details> </div> <div class="section-container"> <details> <summary><h2>Sampler Presets</h2></summary> <div class="info-card"> <div class="card-content"> <p>For a seamless setup in SillyTavern, you can download pre-configured sampler presets. These are tuned to provide an optimal balance between creativity and narrative coherence for this model.</p> <p>Simply download the <code>.json</code> file below and import it into SillyTavern's sampler presets menu.</p> <a href="https://huggingface.co/Darkhn/Samplersettingsandsystemprompt/raw/main/MistralV7TekkenSillyTavernsettings.json" target="_blank" class="button"> Download SillyTavern Presets <span class="link-arrow">→</span> </a> <p><li>For those that dont use silly tavern, Samplers settings are:</li></p> <ul> <p><strong>Temp:</strong> 1</p> <p><strong>Min P:</strong> 0.035</p> </ul> </div> </div> </details> </div>

<div class="section-container"> <details open> <summary> <h2>Roleplay Format Guide</h2> </summary> <div class="info-card"> <div class="card-content"> <p>For the best results, use this structured format. This helps the AI clearly distinguish between actions, inner thoughts, and dialogue.</p> <dl class="format-list"> <dt>Actions / Descriptions</dt> <dd><code>He walked across the room and stared out the window.</code></dd> <dt>Inner Thoughts</dt> <dd><code>-I wonder what she's thinking.-</code></dd> <dt>Dialogue</dt> <dd><code>Alex (Curious): "What do you see out there?"</code></dd> </dl> <p>Standard novel-style formatting is also understood, but this structured format is preferred for clarity.</p> </div> </div> </details> </div> <div class="section-container"> <details> <summary><h2>Roleplay Example</h2></summary> <div class="info-card"> <div class="card-content"> <p>Click the button below to view a full, unedited chatlog demonstrating the model's narrative style and character portrayal.</p> <a href="https://huggingface.co/Darkhn/Samplersettingsandsystemprompt/blob/main/chatlogs/chatlogmistrallarge.png" target="blank" class="button"> View Chatlog Example <span class="link-arrow">→</span> </a> </div> </div> </details> </div> <div class="section-container"> <details open> <summary><h2>Model Description</h2></summary> <div class="info-card"> <div class="card-content"> <p>This is <strong>Version 12.0</strong> in the Animus series. V12.0 is a direct fine-tune of <strong>CrucibleLab-TG/M3.2-36b</strong>, which is an upscaled version of <strong>mistralai/Mistral-Small-3.2-24B-Instruct-2506</strong>.</p> <p>V12.0's strength comes from a novel dataset designed to teach the model the <em>why</em> behind the lore, not just the <em>what</em>. The training data is a mix of:</p> <ul> <li><strong>A 3,000-example Q&A dataset:</strong> This data is framed as an in-character study session, like a student at Jade Mountain Academy learning about the history, relationships, and politics of Pyrrhia's tribes. This provides a deep, contextual understanding of the universe.</li> <li><strong>A 3,000-example uncensored roleplay dataset:</strong> The same high-quality, mature roleplay scenarios used in previous versions, ensuring the model maintains its engaging and dynamic narrative capabilities.</li> </ul> <p>The result is a model with <strong>exceptionally strong prose and a deep grasp of in-universe lore</strong>, making for a highly immersive and accurate roleplaying experience.</p> <p>Note for roleplay, it follows system prompt and first message, meaning if the first assistant message is short, the following messages will be short.</p> </div> </div> </details> </div>

<div class="section-container"> <details open> <summary><h2>Training Details</h2></summary> <div class="info-card"> <div class="info-header"> <h3>V12.0 Training Process</h3> </div> <div class="card-content"> <p>V12.0 marks a shift from model merging to a focused, direct fine-tuning approach using Qlora. This allows for greater control over the final model's characteristics.</p> <ul> <li><strong>Base Model:</strong> CrucibleLab-TG/M3.2-36b</li> <li><strong>Hardware:</strong> 1x NVIDIA RTX Pro 6000 Blackwell</li> <li><strong>Epochs:</strong> 2</li> <li><strong>Method:</strong> Qlora</li> </ul> </div> </div> <div class="info-card"> <div class="info-header"> <h3>Training Dataset</h3> </div> <div class="card-content"> <p>The V12.0 dataset consists of <strong>6,000 high-quality examples</strong>, a combination of two distinct types:</p> <ul> <li><strong>In-Character Q&A (3,000 examples):</strong> This new dataset simulates a student at Jade Mountain Academy studying the world's lore. It's composed of roleplay-style questions and answers covering tribe history, family dynamics, and political relationships. This method builds a foundational, interconnected understanding of the lore.</li> <li><strong>Uncensored Roleplay (3,000 examples):</strong> This is the same mature, canon-centric dataset refined for previous versions. It explores pivotal "what-if" scenarios from the books using only canon characters, ensuring the model can handle complex and dramatic narratives.</li> </ul> <p>Both datasets underwent a rigorous cleaning process to remove formatting artifacts, such as <code>scene transitions</code>, resulting in a cleaner and more natural narrative style.</p> </div> </div> </details> </div>

<div class="section-container"> <details> <summary><h2>Intended Use & Limitations</h2></summary> <div class="info-card"> <div class="card-content"> <ul> <li><strong>Intended Use:</strong> The primary purpose of this model is for creative and roleplaying within the <em>Wings of Fire</em> universe. However, user feedback indicates it is also highly effective for general-purpose roleplaying.</li> <li><strong>Limitations & Quirks:</strong> <ul> <li>Performance on tasks outside of its training domain (general knowledge, coding, etc.) is not guaranteed and will likely be poor.</li> <li><strong>Versatility:</strong> While it appears to be only a <em>Wings of Fire</em> tuned model, users have reported it is very capable of performing normal roleplay with other settings and characters.</li> <li>The model may "hallucinate" or generate plausible but non-canonical information, especially when pushed outside the established "what-if" scenarios.</li> <li><strong>Content:</strong> The training data includes mature and darker themes from the <em>Wings of Fire</em> series, such as conflict, character death, and moral ambiguity. The model is capable of generating content reflecting these themes. As always, it is up to the user what they do with it.</li> <li><strong>Formatting:</strong> Training data was cleaned to remove narrative artifacts like <code>scene transitions</code>. The model should now produce cleaner prose.</li> <li><strong>Safety:</strong> This model has not undergone additional safety alignment beyond what was included in its base model. Standard responsible AI practices should be followed.</li> </ul> </li> </ul> </div> </div> </details> </div> <div class="section-container"> <details> <summary><h2>Acknowledgements</h2></summary> <div class="info-card"> <div class="card-content"> <ul> <li>Credit to mistralai for the powerful Mistral-small-3.2-24b model.</li> <li>Credit to Google for the Gemini Pro model, used in dataset generation.</li> </ul> </div> </div> </details> </div> </div> </div>