title: Command A: An Enterprise-Ready Large Language Model
summary: In this report we describe the development of Command A, a powerful large
  language model purpose-built to excel at real-world enterprise use cases.
  Command A is an agent-optimised and multilingual-capable model, with support
  for 23 languages of global business, and a novel hybrid architecture balancing
  efficiency with top of the range performance. It offers best-in-class Retrieval
  Augmented Generation (RAG) capabilities with grounding and tool use to automate
  sophisticated business processes. These abilities are achieved through a
  decentralised training approach, including self-refinement algorithms and model
  merging techniques. We also include results for Command R7B which shares
  capability and architectural similarities to Command A. Weights for both models
  have been released for research purposes. This technical report details our
  original training pipeline and presents an extensive evaluation of our models
  across a suite of enterprise-relevant tasks and public benchmarks,
  demonstrating excellent performance and efficiency.
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paper_title: Command A: An Enterprise-Ready Large Language Model
paper_summary: In this report we describe the development of Command A, a powerful large
  language model purpose-built to excel at real-world enterprise use cases.
  Command A is an agent-optimised and multilingual-capable model, with support
  for 23 languages of global business, and a novel hybrid architecture balancing
  efficiency with top of the range performance. It offers best-in-class Retrieval
  Augmented Generation (RAG) capabilities with grounding and tool use to automate
  sophisticated business processes. These abilities are achieved through a
  decentralised training approach, including self-refinement algorithms and model
  merging techniques. We also include results for Command R7B which shares
  capability and architectural similarities to Command A. Weights for both models
  have been released for research purposes. This technical report details our
  original training pipeline and presents an extensive evaluation of our models
  across a suite of enterprise-relevant tasks and public benchmarks,
  demonstrating excellent performance and efficiency.
paper_ai_summary: Command A, a multilingual large language model, uses decentralized training with self-refinement and model merging to achieve efficient and top-performing Retrieval Augmented Generation for enterprise use.
paper_ai_keywords: agent-optimised multilingual-capable Retrieval Augmented Generation (RAG) decentralized training self-refinement algorithms model merging techniques