transformers safetensors llama text-generation merge axolotl finetune conversational en base_model:EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1 base_model:merge:EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1 base_model:SicariusSicariiStuff/Negative_LLAMA_70B base_model:merge:SicariusSicariiStuff/Negative_LLAMA_70B base_model:aaditya/Llama3-OpenBioLLM-70B base_model:merge:aaditya/Llama3-OpenBioLLM-70B base_model:invisietch/L3.1-70Blivion-v0.1-rc1-70B base_model:merge:invisietch/L3.1-70Blivion-v0.1-rc1-70B license:llama3.3 autotrain_compatible text-generation-inference endpoints_compatible exl2 region:us
---
base_model:
- SicariusSicariiStuff/Negative_LLAMA_70B
- invisietch/L3.1-70Blivion-v0.1-rc1-70B
- EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1
- aaditya/Llama3-OpenBioLLM-70B
language:
- en
library_name: transformers
license: llama3.3
license_name: llama3.3
tags:
- merge
- axolotl
- finetune
---
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<body>
  <div class="rune-border">
    <div class="vertical-sides"></div>
    <div class="container">
      <h1>Pernicious Prophecy 70B</h1>
      <p>
        <img src="./header.gif" alt="Pernicious Prophecy 70B GIF" />
      </p>
      <h2 style="margin-top: 0em; padding-top: 0em;">Jump Straight In...</h2>
      <p>
        <a href="#settings">Click here for downloads & settings</a>
      </p>
    </div>
    <div class="rune-separator"></div>
    <h2 style='padding-top:0.5em;'>An Introduction...</h2>
    <p>
      <b>Pernicious Prophecy 70B</b> is a Llama-3.3 70B-based, two-step model designed by <a
        href="https://huggingface.co/Black-Ink-Guild">Black Ink Guild</a> (<a 
        href="https://huggingface.co/SicariusSicariiStuff">SicariusSicariiStuff</a> and <a 
        href="https://huggingface.co/invisietch">invisietch</a>) for uncensored roleplay, assistant tasks, and general 
      usage.
    </p>
    <p class="red">
      <b>NOTE:</b> Pernicious Prophecy 70B is an uncensored model and can produce deranged, offensive, and dangerous
      outputs. You are solely responsible for anything that you choose to do with this model.
    </p>
    <p>
      If you have any issues or just want to chat about Pernicious Prophecy &amp; future Black Ink Guild releases, join
      <a href="https://discord.gg/gXQzQcnedb">our Discord server</a>.
    </p>
    <div class="rune-separator"></div>
    <h2 id="settings">Engage the Model...</h2>
    <h3>Model Downloads</h3>
    <p>
      FPX: 
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B">FP16 (HF)</a> |
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B_FP8">FP8 (Aph.)</a>
    </p>
    <p>
      GGUF: 
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B_GGUF_Q4_K_S">Q4_K_S</a> |
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B_GGUF_Q4_K_M">Q4_K_M</a> |
      <a href="https://huggingface.co/mradermacher/Pernicious_Prophecy_70B-GGUF">mradermacher</a>
    </p>
    <p>
      EXL2: 
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B-3.5bpw">3.5bpw</a> |
      <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B-5.0bpw">5.0bpw</a>
    </p>
    <h3>Recommended Settings</h3>
    <p>
      Pernicious Prophecy 70B uses the Llama-3 Instruct format, which is available as a preset in all good UIs. The
      sampler settings used in testing are as follows:
    </p>
    <ul>
      <li><b>Instruct Template</b>: Llama-3 Instruct</li>
      <li><b>Context</b>: 32,768</li>
      <li><b>Temperature</b>: 0.9-1.1</li>
      <li><b>Min P</b>: 0.06-0.12</li>
      <li><b>Rep Pen</b>: 1.07-1.09</li>
      <li><b>Rep Pen Range</b>: 1,536</li>
    </ul>
    <p>
      Feel free to use other sampler settings, these are just sane defaults. XTC is good for roleplaying with the model
      but may not be beneficial for other tasks.
    </p>
    <h3>Context Length</h3>
    <p>
      The model has been tested in roleplays using up to <b>32,768 token context</b> at various quantizations and is
      incredibly stable at this context length.
    </p>
    <p>
      It is possible that the context works at even longer context lengths, but it was not deemed within the parameters
      of our testing.
    </p>
    <div class="rune-separator"></div>
    <h2>Sip the Poison...</h2>
    <p>
      Here, you can find example outputs from the LLM to various instructions. For each of these examples, the model was
      inferenced at fp8 with 1.0 temperature, 0.1 min-p, 1.04 repetition penalty, and all other samplers neutralized.
    </p>
    <ul>
      <li>
        <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B/blob/main/nasa.md">Write a 2000 word, Markdown-formatted, report for NASA. Evaluate each of Jupiter's moons as a suitable 
          colony with pros & cons, then provide a recommendation.</a>
      </li>
      <li>
        <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B/blob/main/tone.md">Write me a 3,000 word opening chapter of a 'gritty hard sci-fi' novel, drawing inspiration from 
          the writing styles of Isaac Asimov & Andy Weir. Use third person personal. Include dialogue and internal monologues. 
          The POV character for the opening chapter should be a 26 year old astronaut called Tone on a mission to Europa, who 
          has just realised that the craft for the return journey is broken beyond repair, and he only has supplies for a few 
          months. Given that survival is impossible, he seeks to spend the few months he has researching titan, so his life 
          &amp; mission are not wasted.</a>
      </li>
      <li>
        <a href="https://huggingface.co/Black-Ink-Guild/Pernicious_Prophecy_70B/blob/main/cookie.md">Build me a basic cookie clicker game in HTML & Javascript.</a><br />
      </li>
    </ul>
    <p>
      These examples were all the best of 2 responses.
    </p>
    <div class="rune-separator"></div>
    <h2>The Codex...</h2>
    <p>
      Here, you can find some useful prompting tips for working with Pernicious Prophecy 70B.
    </p>
    <h3>Formatting</h3>
    <p>
      'Use markdown' and 'use formatting' are likely to produce the best formatted output. We decided to train these on
      trigger words to avoid random Markdown in roleplay replies.
    </p>
    <h3>System Prompting</h3>
    <p>
      Pernicious Prophecy 70V is very sensitive to prompting, even over long context. The more you instruct it, the more 
      it will know what you want it to do.
    </p>
    <p>
      'Avoid purple prose, avoid cliches, avoid deus ex machinae' is a useful prompt snippet for roleplaying purposes.
      For best results, don't use your roleplay prompt when using Pernicious Prophecy as an assistant.
    </p>
    <div class="rune-separator"></div>
    <h2>Assembling the Repertoire...</h2>
    <p>
      We used a two-step process: a merge step to combine the abilities of some of the best L3 70B models on Huggingface
      and a gentle SFT training step to heal the merge and address some issues around refusals and positivity bias.
    </p>
    <h3>The Merge Step</h3>
    <p>
      First, a
      <code>model_stock</code> merge was applied using four high-quality Llama-3 based models:
    <ul>
      <li>
        <b>SicariusSicariiStuff/Negative_LLAMA_70B</b> - chosen to be the base model, because of its low censorship,
        reduced positivity bias, and engaging writing style
      </li>
      <li>
        <b>invisietch/L3.1-70Blivion-v0.1-rc1-70B</b> - added for its exceptional formatting, roleplay performance,
        and general intelligence.
      </li>
      <li>
        <b>EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1</b> - selected for its ability in longer-form storytelling, varied
        outputs, and quality thought.
      </li>
      <li>
        <b>aaditya/Llama3-OpenBioLLM-70B</b> - to add a better understanding of anatomy, and another long-form reasoning
        model to the stack.
      </li>
    </ul>
    </p>
    <h3>The Finetuning Step</h3>
    <p>
      We used a <b>qlora-based</b>, targeted finetune on 2x NVIDIA RTX A6000 GPUs, with a curated dataset of
      approximately 18 million tokens designed to surgically address issues that we identified in the merge.
    </p>
    <p>
      The finetuning took a total of about 14 hours, using Axolotl, and targeted specific high-priority LORA modules
      which allowed us to maintain a 16k sequence length even with 96GB VRAM.
    </p>
    <div class="sidebyside" style="padding-bottom:2em;">
      <a href="https://github.com/arcee-ai/mergekit">
        <img 
          class="badge"
          src="https://huggingface.co/Black-Ink-Guild/READMETEST/resolve/main/mergekit.png" 
          alt="Built with Mergekit" 
          width="200" 
          height="32" 
        />
      </a>
      <a href="https://github.com/axolotl-ai-cloud/axolotl">
        <img 
          class="badge" 
          src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png"
          alt="Built with Axolotl" 
          width="200" 
          height="32" 
        />
    </div>
  </div>
</body>

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