Home ยป Optimizing High-Speed Programming with Databricks’ DBRX LLM Model for GPU Efficiency

Optimizing High-Speed Programming with Databricks’ DBRX LLM Model for GPU Efficiency

Databricks has released the DBRX model, which is an LLM with capabilities close to Gemini Pro 1.0, but excels in speed of answering questions and programming or solving mathematical problems.

DBRX relies on a mixture-of-experts (MoE) framework with a total of 16 sets of expert sub-models, running 4 sets at a time for a total of 132 billion parameters, but actually runs 36 billion parameters at a time. The dataset used is 12 trillion tokens trained with 32k token context windows.

Databricks states that when running DBRX on Mosaic AI Model Serving (an AI company acquired by Databricks), it can generate 150 tokens per second, which is four times more efficient than the previous MPT model in terms of speed, being just slightly below Mixtral, but with significantly better response quality.

The DBRX model released comes in both base and command-receiver versions, with a limited open-source licensing agreement that restricts misuse and prohibits organizations with over 700 million users per month from using it.
Source – Databricks

TLDR: Databricks releases the DBRX model with advanced capabilities in speed, programming, and mathematical problem-solving, based on a mixture-of-experts framework running 132 billion parameters but executing 36 billion parameters at a time, providing high-quality responses.

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