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license: apache-2.0 |
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<title>Aura-llama Data Card</title> |
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code { font-family: 'Courier New', monospace; color: #A3BE8C; } </style> </head> <body> <div class="container"> |
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<div class="header"> |
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<h1>Aura-llama</h1> </div> <div class="info"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/QYpWMEXTe0_X3A7HyeBm0.webp" alt="Aura-llama image"> |
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<p>Now that the cute anime girl has your attention.</p> |
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<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> |
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<p>Aura-llama is a merge of the following models to create a base model to work from:</p> |
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<ul> |
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<li><a href="https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li> |
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<li><a href="https://huggingface.co./meta-llama/Meta-Llama-3-8B-Instruct">meta-llama/Meta-Llama-3-8B-Instruct</a></li> |
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</ul> |
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</div> |
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<div class="update-section"> |
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<h2>Merged Evals (Has Not Been Finetuned):</h2> |
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<p>Aura-llama</p> |
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<ul> |
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<li>Avg: ?</li> |
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<li>ARC: ?</li> |
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<li>HellaSwag: ?</li> |
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<li>MMLU: ?</li> |
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<li>T-QA: ?</li> |
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<li>Winogrande: ?</li> |
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<li>GSM8K: ?</li> |
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</ul> |
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</div> |
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<div class="update-section"> |
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<h2>🧩 Configuration</h2> |
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<pre><code> |
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slices: |
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- sources: |
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- model: meta-llama/Meta-Llama-3-8B-Instruct layer_range: [0, 23] |
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- sources: |
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- model: meta-llama/Meta-Llama-3-8B-Instruct layer_range: [7, 31] |
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merge_method: passthrough |
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dtype: bfloat16 |
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</code></pre> |
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