---
library_name: transformers
tags:
- llama-factory
license: llama3
datasets:
- TheSkullery/Aether-Lite-V1.2
---
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  <title>L3-Aethora-15B Data Card</title>
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      <h1>L3-Aethora-15B</h1>
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    <div class="info">
      <img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/W0qzZK_V1Zt1GdgCIsnrP.png">
      <p>The Skullery Presents L3-Aethora-15B.</p>
      <p><strong>Creator:</strong> <a href="https://huggingface.co/steelskull" target="_blank">Steelskull</a></p>
      <p><strong>Dataset:</strong> <a href="https://huggingface.co/datasets/TheSkullery/Aether-Lite-V1.2" target="_blank">Aether-Lite-V1.2</a></p>
      <p><strong>Trained:</strong> 4 x A100 for 15 hours Using RsLora and DORA</p>
      <h1>About L3-Aethora-15B:</h1>
      <pre><code> L3 = Llama3 </code></pre>
      <p>L3-Aethora-15B was crafted through using the abilteration method to adjust model responses. The model's refusal is inhibited, focusing on yielding more compliant and facilitative dialogue interactions. It then underwent a modified DUS (Depth Up Scale) merge (originally used by @Elinas) by using passthrough merge to create a 15b model, with specific adjustments (zeroing) to 'o_proj' and 'down_proj', enhancing its efficiency and reducing perplexity. This created AbL3In-15b.<br>
      <p>AbL3In-15b was then trained for 4 epochs using Rslora & DORA training methods on the Aether-Lite-V1.2 dataset, containing ~82000 high quality samples, designed to strike a fine balance between creativity, slop, and intelligence at about a 60/40 split</p>  
      <p>This model is trained on the L3 prompt format.</p>
      <h2>Quants:</h2>
        <li><a href="https://huggingface.co/mradermacher/L3-Aethora-15B-GGUF" target="_blank">Mradermacher/L3-Aethora-15B-GGUF</a></li>
        <li><a href="https://huggingface.co/mradermacher/L3-Aethora-15B-i1-GGUF" target="_blank">Mradermacher/L3-Aethora-15B-i1-GGUF</a></li>
        <li><a href="https://huggingface.co/NikolayKozloff" target="_blank">NikolayKozloff/L3-Aethora-15B-GGUF</a></li>
      <p></p>
      <h2>Dataset Summary: (Filtered)</h2>
      <p>Filtered Phrases: GPTslop, Claudism's</p>
      <ul>
        <li><strong>mrfakename/Pure-Dove-ShareGPT:</strong> Processed 3707, Removed 150</li>
        <li><strong>mrfakename/Capybara-ShareGPT:</strong> Processed 13412, Removed 2594</li>
        <li><strong>jondurbin/airoboros-3.2:</strong> Processed 54517, Removed 4192</li>
        <li><strong>PJMixers/grimulkan_theory-of-mind-ShareGPT:</strong> Processed 533, Removed 6</li>
        <li><strong>grimulkan/PIPPA-augmented-dedup:</strong> Processed 869, Removed 46</li>
        <li><strong>grimulkan/LimaRP-augmented:</strong> Processed 790, Removed 14</li>
        <li><strong>PJMixers/grimulkan_physical-reasoning-ShareGPT:</strong> Processed 895, Removed 4</li>
        <li><strong>MinervaAI/Aesir-Preview:</strong> Processed 994, Removed 6</li>
        <li><strong>Doctor-Shotgun/no-robots-sharegpt:</strong> Processed 9911, Removed 89</li>
      </ul>
      <h2>Deduplication Stats:</h2>
      <p>Starting row count: 85628, Final row count: 81960, Rows removed: 3668</p>
    <p><strong>I've had a few people ask about donations so here's a link:</strong</p>
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