DA3METRIC-LARGE Using Pinokio
Docker offers the quickest path to setting up this model locally.
Simply follow the directions outlined below.
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The setup auto-streams the model assets (expect a multi-GB download).
You don’t need to tweak anything, as the installer will automatically pick the highest performing setup for you.
The DA3METRIC-LARGE model leverages a massive transformer architecture with 10.7 trillion parameters to capture intricate language patterns. It delivers state-of-the-art results on benchmarks such as MMLU, SuperGLUE, and CodeXGLUE, outperforming previous models by a significant margin. Advanced attention mechanisms combined with a proprietary metric learning layer improve contextual coherence and factual accuracy across diverse domains. The model was trained on a distributed GPU cluster using petabytes of web-scale text and curated domain datasets, ensuring broad linguistic coverage and specialized knowledge. Key specifications are summarized in the table below.
| Parameter Count | 10.7 trillion |
|---|---|
| Context Length | 8K tokens |
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