Vortex5/Gemma-4-26B-A4B-Animus-V14.1-FFT-heretic
This is a decensored version of Darkhn/Gemma-4-26B-A4B-Animus-V14.1-FFT, made using Heretic v1.2.0 with the Arbitrary-Rank Ablation (ARA) method (with row-norm preservation)
Abliteration parameters
Performance
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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>Gemma-4-26B-A4B-Animus-V14.1-FFT</h1> </div> <div class="info"> <img src="image.gif" alt="WingsofFire" width="700">
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<div class="section-container"> <details open> <summary><h2>Critical: Chat Template & Setup</h2></summary> <div class="info-card"> <div class="card-content"> <p>This model uses the standard <strong>Gemma 4</strong> chat template. The structure is complex and requires specific configuration for correct performance. Please read the following sections carefully.</p> <p><strong>Human-Readable Format:</strong></p> <pre><code><bos><|turn>system <|think|> {system prompt}<turn|> <|turn>user {user message}<turn|> <|turn>model <|channel>thought {reasoning}<channel|>{response}<turn|></code></pre> </div> </div> <div class="info-card"> <div class="info-header"><h3>⚠️ Important: Use Chat Completion, Not Text Completion</h3></div> <div class="card-content"> <p><strong>Strongly recommended:</strong> Always use the <code>/v1/chat/completions</code> endpoint. Correct formatting is handled automatically by the server.</p> <p>Text completion (<code>/v1/completions</code>) is currently broken for impersonations without a custom patch. Sending the context as a user prompt and asking the model to generate the response can produce a malformed turn structure.</p> <p><strong>Reasoning with text completion and TabbyAPI/Llama.cpp specific: </strong>You must prefill the response with <code>startreplywith: <|channel>thought + \n</code> (a new line) or reasoning will not trigger (you will get blank responses if you enabled reasoning and did not prefill)</p> </div> </div> <div class="info-card"> <div class="info-header"><h3>Chat Completion API Configuration (SillyTavern, etc.)</h3></div> <div class="card-content"> <p>When using an OpenAI-compatible API, you must add custom parameters to control thinking and ensure correct token handling. In frontends like <strong>SillyTavern</strong>, add the following JSON to the <strong>"Custom Parameters"</strong> (or <code>extrabody</code>) field in your connection settings:</p> <pre><code>"chattemplatekwargs": {"enablethinking": true} "skipspecialtokens": false</code></pre> <ul> <li><code>"enablethinking": true</code>: Activates the model's chain-of-thought reasoning. Change to <code>false</code> to disable it for faster, more direct responses.</li> <li><code>"skipspecialtokens": false</code>: <strong>This is critical.</strong> It prevents the API from stripping away the special tokens (like <code><|channel></code> and <code><channel|></code>) that are required for the model's chat template to work correctly.</li> </ul> </div> </div> <div class="info-card"> <div class="info-header"><h3>General Notes</h3></div> <div class="card-content"> <ul> <li>The model retains the vision adapter from the base Gemma 4 26B A4B and supports image inputs.</li> <li>Both thinking and no-thinking modes were included in training data — use <code>enablethinking</code> to select at runtime.</li> <li>The <code><|think|></code> token in the system turn is what activates chain-of-thought reasoning at the architecture level.</li> </ul> </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-3/Gemma-4-26B-A4B-Animus-V14.1-FFT-GGUF" target="blank" class="button"> Download GGUF Files <span class="link-arrow">→</span> </a> <a href="https://huggingface.co/Darkhn-Quants-3/Gemma-4-26B-A4B-Animus-V14.1-FFT-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/Gemma4ThinkSillyTavernsettings.json" target="blank" class="button"> Download SillyTavern Preset (Thinking) <span class="link-arrow">→</span> </a> <a href="https://huggingface.co/Darkhn/Samplersettingsandsystemprompt/raw/main/Gemma4NoThinkSillyTavernsettings.json" target="blank" class="button"> Download SillyTavern Preset (No Thinking) <span class="link-arrow">→</span> </a> <p><li>For those that dont use silly tavern, Samplers settings are:</li></p> <ul> <p><strong>Temperature:</strong> 1.0</p> <p><strong>Min P:</strong> 0.02</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 14.1</strong>, in the Animus series. V14.1 is built on <strong>google/gemma-4-26B-A4B-it</strong>, offering a massive leap in parameter count and underlying logic compared to previous versions.</p> <p>V14.1'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 has been heavily expanded for this version:</p> <ul> <li><strong>Base Samples Doubled:</strong> The foundation of in-character study sessions and uncensored roleplays has been doubled in size (14,000) to deepen contextual understanding.</li> <li><strong>1,000 Instruction Q&A Samples:</strong> Additional Wings of Fire-based instruction formatting.</li> <li><strong>1,000 NSFW/BAD Ending Samples:</strong> Non-Wings of Fire scenarios added to diversify narrative flexibility and handle darker, complex outcomes.</li> <li><strong>Reasoning (2000 examples):</strong> COT reasoning, in a dungeonmaster style, the reasoning blocks are used as the dungeonmaster notes.</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>V14.1 Training Process</h3> </div> <div class="card-content"> <p>V14.1 Was Fully fine-tuned with the vison layers frozen, and not is not a Lora adapter.</p> <ul> <li><strong>Base Model:</strong> google/gemma-4-26B-A4B-it</li> <li><strong>Hardware:</strong> 8 x B200</li> <li><strong>Epochs:</strong> 3</li> </ul> </div> </div> <div class="info-card"> <div class="info-header"> <h3>Training Dataset</h3> </div> <div class="card-content"> <p>The V14.0 dataset has been significantly expanded from previous versions:</p> <ul> <li><strong>Doubled Base Dataset (14,000 examples):</strong> The original foundation of In-Character Q&A and Uncensored Roleplay examples was doubled to reinforce the lore foundation and enhance roleplay quality.</li> <li><strong>Instruction Q&A (1,000 examples):</strong> Additional Wings of Fire-based instruction Q&A sets.</li> <li><strong>NSFW / Bad Endings (1,000 examples):</strong> Non-Wings of Fire scenarios specifically targeting mature themes and bad endings to widen the model's range of dramatic narrative capabilities.</li> <li><strong>Reasoning (2000 examples):</strong> COT reasoning, in a dungeonmaster style, the reasoning blocks are used as the dungeonmaster notes.</li> </ul> <p>All datasets underwent a rigorous cleaning process to remove formatting artifacts, 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 Google for the powerful gemma-4-26B-A4B-itt model.</li> <li>Credit to Google for the Gemini Pro model, used in dataset generation.</li> <li>Credit to Anthropic for sonnet 4.5, used in dataset generation.</li> <li>Credit to Hangzhou DeepSeek Artificial Intelligence for the deepseek model, used in dataset generation.</li> <li>Credit to Moonshot AI for the Kimi K2 model, used in dataset generation.</li> </ul> </div> </div> </details> </div>
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