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Toward End-to-End MLOps Tools Map: A Preliminary Study based on a Multivocal Literature Review
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MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tools often create confusion on the most appropriate tool to be used in each DevOps phase. To overcome this issue, we conducted a multivocal literature review mapping 84 MLOps tools identified from 254 Primary Studies, on the DevOps phases, highlighting their purpose, and possible incompatibilities. The result of this work will be helpful to both practitioners and researchers, as a starting point for future investigations on MLOps tools, pipelines, and processes.
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Towards a Small Language Model Lifecycle Framework
A synthesis proposing a modular lifecycle framework that organizes Small Language Model development and deployment into interconnected main, optional, and cross-cutting components.
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