The fastest tactical way to launch this model locally is via a Docker image.
Check out the detailed setup guide below to begin.
The installer auto-downloads and deploys the entire model pack.
The automated script takes care of everything, tailoring the setup to your specs.
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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- Downloader pulling custom upscaler pipelines like SUPIR for local forge
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