Mistral unveils Timestral, models for forecasting time series; the largest has 209 million parameters
Prepared by Sintelligent with the help of SI. Published in SI: . Updated: .
A small model that also runs on an ordinary processor can forecast number series as well as larger ones, and forecasts are becoming cheaper.
According to Mistral, Timestral is a family of four models (from 5 to 209 million parameters) for probabilistic multivariate forecasts without fine-tuning: sensor readings, load, payment flows and the like. The company says the largest model ranks first on three public benchmarks — GIFT-Eval, TIME and fev-bench — with two-thirds of the previous leader's parameters. It accepts up to 32,768 steps of history and forecasts up to 1,024 steps in one pass; it also runs on CPUs. The source code is published on GitHub and the weights of the largest model on Hugging Face; results have been submitted to the GIFT-Eval and TIME leaderboards.
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