DBRX is a fine-grained mixture-of-experts (MoE) architecture that provides substantial improvements in compute-efficiency for training and inference. It surpasses GPT-3.5 and is competitive with Gemini 1.0 Pro.
DBRX uses a fine-grained MoE architecture, which provides substantial improvements in compute-efficiency for training and inference.
DBRX is a transformer-based decoder-only large language model that was trained using next-token prediction.
DBRX has 132B total parameters, of which 36B parameters are active on any input.
DBRX was trained on 3072 NVIDIA H100s connected by 3.2Tbps Infiniband.
DBRX was trained using a suite of Databricks tools, including Unity Catalog, Apache Spark, and Databricks notebooks.
Natural Language Processing (NLP)
Code Modeling
Mathematics and Problem Solving
Conversational AI
Get started with DBRX on Databricks by downloading the model from the Databricks Marketplace
Deploy the model on Model Serving for production applications
Use the Databricks Foundation Model APIs for pay-as-you-go pricing and query the model from the AI Playground chat interface