Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language Model. (arXiv:2211.02001v1 [cs.LG])

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 ranging from equipment manufacturing to
energy-based operational …

arxiv bloom carbon carbon footprint language language model