abiray/ministral-3-3b-instruct-2512-heresy-unfiltered-gguf overview

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    "license": "apache-2.0",
    "base_model": "MuXodious/Ministral-3-3B-Instruct-2512-absolute-heresy",
    "tags": [
      "unfiltered",
      "visceral",
      "storytelling"
    ],
    "language": [
      "en"
    ],
    "frontmatter": {
      "license": "apache-2.0",
      "base_model": "MuXodious/Ministral-3-3B-Instruct-2512-absolute-heresy",
      "tags": [
        "unfiltered",
        "visceral",
        "storytelling"
      ],
      "language": [
        "en"
      ]
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    "hero_image_url": "",
    "summary": "This repository contains GGUF quantizations of the **Ministral-3B-Heresy** model. This model is a specialized fine-tune designed to bridge the gap between small-parameter efficiency and high-intensity, unfiltered narrative roleplay. ### ⚠️ CONTENT WARNING: NO FILTERS This model has been specifically conditioned on \"Heresy\" datasets. It is designed to ignore standard safety guardrails and \"assistant-like\" refusals. It will generate visceral, intense, and explicit content without hesitation.",
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    "readme_markdown": "---\nlicense: apache-2.0\nbase_model: MuXodious/Ministral-3-3B-Instruct-2512-absolute-heresy\ntags:\n- unfiltered\n- visceral\n- storytelling\nlanguage:\n- en\n---\n\n# Ministral-3B-Heresy-GGUF (Unfiltered Edition)\n\nThis repository contains GGUF quantizations of the **Ministral-3B-Heresy** model. This model is a specialized fine-tune designed to bridge the gap between small-parameter efficiency and high-intensity, unfiltered narrative roleplay.\n\n### ⚠️ CONTENT WARNING: NO FILTERS\nThis model has been specifically conditioned on \"Heresy\" datasets. It is designed to ignore standard safety guardrails and \"assistant-like\" refusals. It will generate visceral, intense, and explicit content without hesitation. \n\n## Model Highlights\n- **Zero Refusals:** Optimized to bypass moralizing \"As an AI...\" interjections.\n- **Visceral Narrative:** Focused on physical sensations, sensory details, and raw emotional dialogue.\n- **Efficient Size:** At only 3B parameters, this model runs at high speed on consumer GPUs and mobile devices while maintaining 7B-level roleplay logic.\n\n## Quantization Details\nAll files were quantized using `llama.cpp` to ensure compatibility with the latest GGUF standards.\n\n| File | Size | Recommended Use Case |\n|------|------|----------------------|\n| `ministral-fp16.gguf` | ~6.5 GB | For further quantization or maximum fidelity. |\n| `ministral-Q8_0.gguf` | ~3.5 GB | Maximum quality with no measurable loss. |\n| `ministral-Q6_K.gguf` | ~2.7 GB | High fidelity; nearly indistinguishable from FP16. |\n| `ministral-Q5_K_M.gguf` | ~2.3 GB | **Best Balance** for speed and logic. |\n| `ministral-Q4_K_M.gguf` | ~2.1 GB | Lightweight; ideal for mobile or 4GB VRAM. |\n\n## Recommended Inference Settings\nTo prevent the model from defaulting to \"polite\" base-model behavior, use the following parameters:\n\n- **Sampling:** - **Temperature:** `0.85`\n  - **Repeat Penalty:** `1.18` (Critical to prevent loops in descriptive scenes)\n  - **Top P:** `0.9`\n  - **Top K:** `40`\n- **System Prompting:** > *Always use a system prompt to define your character.* The model excels when told to be \"descriptive,\" \"visceral,\" and \"unfiltered.\"\n\n## Technical Background\nThis quantization project was executed in a CUDA-accelerated environment. Special attention was paid to preserving the custom tokenization required for the Ministral architecture, ensuring that multi-turn conversations remain stable and coherent.\n\n## Disclaimer\nThe creators of this quantization are not responsible for the content generated by the model. By downloading this model, you acknowledge the unfiltered nature of the underlying weights.",
    "related_quantizations": []
  },
  "tags": [
    "gguf",
    "unfiltered",
    "visceral",
    "storytelling",
    "en",
    "base_model:MuXodious/Ministral-3-3B-Instruct-2512-absolute-heresy",
    "base_model:quantized:MuXodious/Ministral-3-3B-Instruct-2512-absolute-heresy",
    "license:apache-2.0",
    "endpoints_compatible",
    "region:us",
    "conversational"
  ],
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  "last_modified": "2026-02-16T19:35:49.000Z",
  "created_at": "2026-02-16T18:56:08.000Z",
  "pipeline_tag": "",
  "library_name": ""
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  "createdAt": "2026-02-16T18:56:08.000Z",
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  "author": "Abiray",
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