flâneur

google-research/timesfm: TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. ·

github.com · 1,103 words · saved by 1 readers

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. This open version is not an officially supported Google product. Latest Model Version: TimesFM 3.0 Archived Model Versions: TimesFM 3.0 is out! TimesFM 3.0 introduces native multivariate time-series forecasting, flexible covariate support (both past-only and past-and-future covariates), superior zero-shot generalist capabilities, and top performance across all three major time-series foundation model benchmarks. Important: The TimesFM source code in this repository is licensed under Apache-2.0, and model weights up to version 2.5 remain Apache-2.0. However, for the time being, TimesFM 3.0 pretrained weights are distributed under the separate timesfm-non-commercial-license-v1.0 license and are restricted to

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting. Paper: A decoder-only foundation model for time-series forecasting, ICML 2024. (NEW!) TimesFM 3.0 Checkpoint: google/timesfm-3.0-pytorch. Checkpoints (up to 2.5): TimesFM Hugging Face Collection. Google Research blog (New blog post for TimesFM 3.0 coming soon!). TimesFM in Google 1P Products: BigQuery ML: Enterprise level SQL queries for scalability and reliability. Google Sheets: For your daily spreadsheet. Vertex Model Garden: Dockerized…

saved by

related reading