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README.md
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library_name: transformers
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tags:
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- llama-factory
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---
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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library_name: transformers
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tags:
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- llama-factory
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license: llama3
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datasets:
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- TheSkullery/Aether-Lite-V1.2
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---
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<!DOCTYPE html>
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<style>
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body {
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font-family: 'Quicksand', sans-serif;
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background: linear-gradient(135deg, #2E3440 0%, #1A202C 100%);
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color: #D8DEE9;
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margin: 0;
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padding: 0;
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font-size: 16px;
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}
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.container {
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width: 80% auto;
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max-width: 1080px auto;
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margin: 20px auto;
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background-color: rgba(255, 255, 255, 0.02);
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padding: 20px;
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border-radius: 12px;
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box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2);
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backdrop-filter: blur(10px);
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border: 1px solid rgba(255, 255, 255, 0.1);
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}
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.header h1 {
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font-size: 28px;
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color: #ECEFF4;
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margin: 0 0 20px 0;
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text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
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}
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.update-section {
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margin-top: 30px;
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}
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.update-section h2 {
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font-size: 24px;
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color: #88C0D0;
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}
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.update-section p {
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font-size: 16px;
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line-height: 1.6;
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color: #ECEFF4;
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}
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.info img {
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width: 100%;
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border-radius: 10px;
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margin-bottom: 15px;
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}
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a {
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color: #88C0D0;
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text-decoration: none;
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}
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a:hover {
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color: #A3BE8C;
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}
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.button {
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display: inline-block;
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background-color: #5E81AC;
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color: #E5E9F0;
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padding: 10px 20px;
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border-radius: 5px;
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cursor: pointer;
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text-decoration: none;
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}
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.button:hover {
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background-color: #81A1C1;
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}
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pre {
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background-color: #2E3440;
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padding: 10px;
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border-radius: 5px;
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overflow-x: auto;
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}
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code {
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font-family: 'Courier New', monospace;
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color: #D8DEE9;
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}
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</style>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>L3-Aethora-15B Data Card</title>
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<link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>L3-Aethora-15B</h1>
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</div>
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<div class="info">
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<img src="https://cdn-uploads.huggingface.co/your-uploaded-image-link.png">
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<p>The Skullery Presents L3-Aethora-15B.</p>
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<p><strong>Creator:</strong> <a href="https://huggingface.co/steelskull" target="_blank">Steelskull</a></p>
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<h1>About L3-Aethora-15B:</h1>
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<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 underwent a specialized merging process (originally used by @Elias) by using passthrough merge to create a 15b model, with specific adjustments to 'o_proj' and 'down_proj' settings, enhancing its efficiency and reducing perplexity. This created AbL3In-15b.<br>
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<p>AbL3In-15b was then fine-tuned on the Aether-Lite-V1 dataset, containing ~82000 high quality samples, designed to strike a fine balance between creativity, slop, and intelligence at about a 60/40 split</p>
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<p>Filtered Phrases: GPTslop, Claudism's</p>
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<h2>Dataset Summary: (Filtered)</h2>
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<ul>
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<li><strong>mrfakename/Pure-Dove-ShareGPT:</strong> Processed 3707, Removed 150</li>
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<li><strong>mrfakename/Capybara-ShareGPT:</strong> Processed 13412, Removed 2594</li>
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<li><strong>jondurbin/airoboros-3.2:</strong> Processed 54517, Removed 4192</li>
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<li><strong>PJMixers/grimulkan_theory-of-mind-ShareGPT:</strong> Processed 533, Removed 6</li>
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<li><strong>grimulkan/PIPPA-augmented-dedup:</strong> Processed 869, Removed 46</li>
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<li><strong>grimulkan/LimaRP-augmented:</strong> Processed 790, Removed 14</li>
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<li><strong>PJMixers/grimulkan_physical-reasoning-ShareGPT:</strong> Processed 895, Removed 4</li>
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<li><strong>MinervaAI/Aesir-Preview:</strong> Processed 994, Removed 6</li>
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<li><strong>Doctor-Shotgun/no-robots-sharegpt:</strong> Processed 9911, Removed 89</li>
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</ul>
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<h2>Deduplication Stats:</h2>
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<p>Starting row count: 85628, Final row count: 81960, Rows removed: 3668</p>
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</div>
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</div>
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</body>
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</html>
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