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license: apache-2.0
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<title>Aura-llama Data Card</title>
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<h1>Aura-llama</h1> </div> <div class="info">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/QYpWMEXTe0_X3A7HyeBm0.webp" alt="Aura-llama image">
<p>Now that the cute anime girl has your attention.</p>
<p>Aura-llama is using the methodology presented by SOLAR for scaling LLMs called depth up-scaling (DUS), which encompasses architectural modifications with continued pretraining. Using the solar paper as a base, I integrated Llama-3 weights into the upscaled layers, and In the future plan to continue training the model.</p>
<p>Aura-llama is a merge of the following models to create a base model to work from:</p>
<ul>
<li><a href="https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li>
<li><a href="https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li>
</ul>
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<h2>Merged Evals (Has Not Been Finetuned):</h2>
<p>Aura-llama</p>
<ul>
<li>Avg: ?</li>
<li>ARC: ?</li>
<li>HellaSwag: ?</li>
<li>MMLU: ?</li>
<li>T-QA: ?</li>
<li>Winogrande: ?</li>
<li>GSM8K: ?</li>
</ul>
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<h2>🧩 Configuration</h2>
<pre><code>
slices:
- sources:
- model: meta-llama/Meta-Llama-3-8B-Instruct layer_range: [0, 23]
- sources:
- model: meta-llama/Meta-Llama-3-8B-Instruct layer_range: [7, 31]
merge_method: passthrough
dtype: bfloat16
</code></pre>
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