Dans-PersonalityEngine-V1.3.0-24b-absolute-heresy

This is a Dans-PersonalityEngine-V1.3.0-24b fine-tune, produced through P-E-W's Heretic (v1.1.0) abliteration engine merged with the Magnitude-Preserving Orthogonal Ablation PR.

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<img src="https://img.shields.io/badge/HERESY_INDEX-ABSOLUTE-white?style=flat-square&labelColor=101010" align="right" width="250">

Heretication Results

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Degree of Heretication

The Heresy Index weighs the resulting model's corruption by the process (KL Divergence) and its abolition of doctrine (Refusals) for a final verdict in classification.

Note: This is an arbitrary classification inspired by Warhammer 40K, having no tangible indication towards the model's performance.

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<!doctype html> <html lang="en"> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <title>Dans-PersonalityEngine-V1.3.0-24b</title> </head> <div class="crt-container"> <div class="crt-case"> <div class="crt-inner-case"> <div class="crt-bezel"> <div class="terminal-screen"> <div style="text-align: center"> <h2>Dans-PersonalityEngine-V1.3.0-24b</h2> <pre class="code-block" style="display: inline-block; text-align: left; font-size: clamp(2px, 0.8vw, 14px); line-height: 1.2; max-width: 100%; overflow: hidden; white-space: pre;"> ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢀⠀⠄⠀⡂⠀⠁⡄⢀⠁⢀⣈⡄⠌⠐⠠⠤⠄⡀⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⡄⠆⠀⢠⠀⠛⣸⣄⣶⣾⡷⡾⠘⠃⢀⠀⣴⠀⡄⠰⢆⣠⠘⠰⠀⡀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠃⠀⡋⢀⣤⡿⠟⠋⠁⠀⡠⠤⢇⠋⠀⠈⠃⢀⠀⠈⡡⠤⠀⠀⠁⢄⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠁⡂⠀⠀⣀⣔⣧⠟⠋⠀⢀⡄⠀⠪⣀⡂⢁⠛⢆⠀⠀⠀⢎⢀⠄⢡⠢⠛⠠⡀⠀⠄⠀⠀ ⠀⠀⡀⠡⢑⠌⠈⣧⣮⢾⢏⠁⠀⠀⡀⠠⠦⠈⠀⠞⠑⠁⠀⠀⢧⡄⠈⡜⠷⠒⢸⡇⠐⠇⠿⠈⣖⠂⠀ ⠀⢌⠀⠤⠀⢠⣞⣾⡗⠁⠀⠈⠁⢨⡼⠀⠀⠀⢀⠀⣀⡤⣄⠄⠈⢻⡇⠀⠐⣠⠜⠑⠁⠀⣀⡔⡿⠨⡄ ⠈⠂⠀⠆⠀⣼⣾⠟⠀⠑⠀⡐⠗⠉⠀⠐⠶⣤⡵⠋⠀⠠⠹⡌⡀⠘⠇⢠⣾⡣⣀⡴⠋⠅⠈⢊⠠⡱⡀ ⠪⠑⢌⠂⣼⣿⡟⠀⠀⠙⠀⠀⠀⡀⠀⠀⠐⡞⡐⠀⠀⡧⠀⢀⠠⠀⣁⠾⡇⠀⠙⡁⠀⠀⢀⣨⣄⡠⢱ ⣸⠈⠊⠙⣛⣿⡧⠔⠚⠛⠳⣄⣀⡬⠤⠬⠼⡣⠃⠀⢀⡗⠀⡤⠞⠙⠄⠂⠃⢀⣠⣤⠶⠙⠅⠁⠃⠋⠈ ⢋⠼⣀⠰⢯⢿⠁⠀⢢⠀⠀⢐⠋⡀⠀⠈⠁⠀⣀⣰⠏⠒⠙⠈⠀⣀⡤⠞⢁⣼⠏⠘⢀⣀⢤⢤⡐⢈⠂ ⠀⠢⠀⠀⠸⣿⡄⠲⠚⠘⠚⠃⢀⠀⠈⢋⠶⠛⠉⠉⢃⣀⢤⢾⠋⣁⡤⡚⠁⢹⠁⠠⢛⠠⠬⠁⢬⠀⠀ ⠀⠈⢳⣒⠋⠉⣿⢐⠠⣀⣃⠀⠀⠉⠂⢁⣀⣀⡤⢞⠩⢑⡨⠰⡞⠁⠁⢀⡠⠾⠎⡈⡌⡈⡓⡀⠄⠀⠀ ⠀⠀⠀⠉⠘⠃⢻⡒⠦⢼⣿⣛⣻⣿⡷⢄⣀⣀⣠⣴⢾⣿⣆⣡⡄⣠⣪⡿⣷⣾⣷⣧⡡⠅⣇⠍⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠙⠒⠒⠛⠛⠓⠉⢹⠀⣷⠴⣻⣽⡻⢧⢻⡿⡏⣼⢿⣻⢾⣿⣿⣿⡿⢠ ⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠈⠂⠻⠨⠰⢋⡅⠉⣑⡇⡗⣿⢂⣸⡿⣿⣛⠿⠃⠁ ⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠳⣌⣙⣸⢧⣿⣕⣼⣇⢹⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⣠⣸⢧⢟⢟⡟⣾⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⢰⠙⣾⡟⣻⡕⣹⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⢸⢰⡏⢠⡿⠾⠋⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⢸⢸⠸⡇⡏⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠸⢸⢸⡇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ ⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠘⠇⡇⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀ </pre> </div> <p> Dans-PersonalityEngine is a versatile model series fine-tuned on 50+ specialized datasets, designed to excel at both creative tasks (like roleplay and co-writing) and technical challenges (such as code generation, tool use, and complex reasoning). </p> <p> V1.3.0 introduces multilingual capabilities with support for 10 languages and enhanced domain expertise across multiple fields. The primary language is still English and that is where peak performance can be expected. </p> <h3>Multilingual Support</h3> <pre class="code-block"> Arabic Chinese English French German Hindi Japanese Korean Portuguese Spanish</pre> <h3>Key Details</h3> <pre class="code-block"> BASE MODEL: mistralai/Mistral-Small-3.1-24B-Base-2503 LICENSE: apache-2.0 LANGUAGE: Multilingual with 10 supported languages CONTEXT LENGTH: 32768 tokens, 131072 with degraded recall</pre> <h3>Recommended Settings</h3> <pre class="code-block"> TEMPERATURE: 1.0 TOP_P: 0.9</pre> <h3>Prompting Format</h3> <p> The model uses the following format I'll refer to as "DanChat-2": </p> <pre class="code-block"> <|system|>system prompt<|endoftext|><|user|>Hi there!<|endoftext|><|assistant|>Hey, how can I help?<|endoftext|></pre> <h3>Why not ChatML?</h3> <p> While ChatML is a standard format for LLMs, it has limitations. DanChat-2 uses special tokens for each role, this reduces biases and helps the model adapt to different tasks more readily. </p> <h3>SillyTavern Template</h3> <p> <a href="https://huggingface.co/PocketDoc/Dans-PersonalityEngine-V1.3.0-24b/resolve/main/resources/DanChat-2.json?download=true" download target="_blank" rel="noopener noreferrer" > Download Master JSON </a> </p> <h3>Inference Provider</h3> <p> This model and others are available from ⚡Mancer AI for those interested in high quality inference without owning or renting expensive hardware. </p> <p class="mancer-button-container"> <a href="https://mancer.tech/" target="_blank" rel="noopener noreferrer" class="mancer-button" > <span class="mancer-text">mancer</span> </a> </p> <h3>Training Process</h3> <p> The model was trained using Axolotl on 8x H100 GPUs for 50 hours. The resources to train this model were provided by Prime Intellect and Kalomaze. </p> <h3>Support Development</h3> <p> Development is limited by funding and resources. To help support: </p> <p>- Contact on HF</p> <p>- Email: [email protected]</p> <p class="coffee-container"> <a href="https://www.buymeacoffee.com/visually" target="_blank" rel="noopener noreferrer" > <img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" height="45" width="162" /> </a> </p> </div> </div> </div> </div> </div> <style> @import url("https://fonts.googleapis.com/css2?family=Consolas&display=swap"); .crt-container { padding: 10px; max-width: 1000px; margin: 0 auto; width: 95%; } .crt-case { background: #e8d7c3; border-radius: 10px; padding: 15px; box-shadow: inset -2px -2px 5px rgba(0, 0, 0, 0.3), 2px 2px 5px rgba(0, 0, 0, 0.2); } .crt-inner-case { background: #e8d7c3; border-radius: 8px; padding: 3px; box-shadow: inset -1px -1px 4px rgba(0, 0, 0, 0.3), 1px 1px 4px rgba(0, 0, 0, 0.2); } .crt-bezel { background: linear-gradient(145deg, #1a1a1a, #2a2a2a); padding: 15px; border-radius: 5px; border: 3px solid #0a0a0a; position: relative; box-shadow: inset 0 0 20px rgba(0, 0, 0, 0.5), inset 0 0 4px rgba(0, 0, 0, 0.4), inset 2px 2px 4px rgba(255, 255, 255, 0.05), inset -2px -2px 4px rgba(0, 0, 0, 0.8), 0 0 2px rgba(0, 0, 0, 0.6), -1px -1px 4px rgba(255, 255, 255, 0.1), 1px 1px 4px rgba(0, 0, 0, 0.3); 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