Cohere announces Command R7B, a lightweight, fast, and enterprise-ready multilingual 7B-parameter model suitable for real-time chatbots and AI agents. Additionally, methods to train classical ML models on large datasets, such as using big-data frameworks like Spark MLlib or the Random Patches approach, are discussed. Random Patches, which involves sampling data patches for tree-based models, often performs better than traditional random forests in certain cases.
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Cohere's Command R7B LLM: Lightweight, fast, and built for enterprises [Open-weights]Train classical ML models on large datasets Formulating and Implementing XGBoost From ScratchSort: