no code implementations • LREC 2022 • Julien Launay, E. L. Tommasone, Baptiste Pannier, François Boniface, Amélie Chatelain, Alessandro Cappelli, Iacopo Poli, Djamé Seddah
We fit a scaling law for compute for the French language, and compare it with its English counterpart.
no code implementations • NeurIPS Workshop ICBINB 2021 • Amélie Chatelain, Amine Djeghri, Daniel Hesslow, Julien Launay, Iacopo Poli
Recent work has identified simple empirical scaling laws for language models, linking compute budget, dataset size, model size, and autoregressive modeling loss.
1 code implementation • 15 Jun 2020 • Amélie Chatelain, Giuseppe Luca Tommasone, Laurent Daudet, Iacopo Poli
In this work, we focus on the identification of such events given many noisy observables.