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  • Alexandra Sasha Luccioni, Sylvain Viguie...
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    Nov 3rd, 2022
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    preprint
    Alexandra Sasha Luccioni, Sylvain Viguie...
    Nov 3rd, 2022

    Progress in machine learning (ML) comes with a cost to the environment, given that training ML models requires significant computational resources, energy and materials. In the present article, we aim to quantify the carbon footprint of BLOOM, a 176-billion parameter language model, across its life cycle. We estimate that BLOOM's final training emitted approximately 24.7 tonnes of~\carboneq~if we consider only the dynamic power consumption, and 50.5 tonnes if we account for all processes...

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