Yacine Jernite
Leads the ML and Society team at Hugging Face; co-author of the Transformers and StarCoder2 papers
- Leads the ML and Society team, Hugging Face1
Yacine Jernite leads the ML and Society team at Hugging Face, working on ML systems governance at the intersection of regulatory and technical tools. Jernite's work has focused on NLP models and on data curation, documentation, and governance, including serving as co-organizer and data area chair for the BigScience workshop, whose ROOTS corpus was used to train the BLOOM model. Jernite is a co-author of the paper that introduced Hugging Face's Transformers library, the StarCoder2 paper, and "Power Hungry Processing" (2023), which compared the energy and carbon cost of deploying task-specific and general-purpose ML models.1234
Work
TransformersPublished research
Co-author of the 2019 paper introducing Hugging Face's Transformers library (arXiv 1910.03771).2
StarCoder2Published research
Co-author of "StarCoder 2 and The Stack v2: The Next Generation" (2024).3
BigScience data curation and governance
Co-organizer and data area chair for the BigScience workshop on large language models, whose ROOTS corpus was used to train BLOOM, according to Jernite's homepage.1
Power Hungry Processing: Watts Driving the Cost of AI Deployment? (external site: arxiv.org)Published research
Co-author, with Sasha Luccioni and Emma Strubell, of a systematic comparison of the inference energy and carbon cost of task-specific and general-purpose ML models.4
This profile covers public professional work only, from the sources below. It is not an endorsement or a ranking. To correct or remove it, use the correction form.