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Google's 200M-parameter time-series foundation model with 16k context

Quality: 8/10 Relevance: 9/10

Summary

TimesFM is a decoder-only time-series foundation model from Google Research optimized for forecasting, now with 200M parameters and a 16k context window in its 2.5 release. The update adds covariate support, an enhanced inference API, and broader ecosystem integration (Hugging Face, BigQuery), while remaining open-source though not an official Google product. The article provides release notes, installation guidance, and example code to experiment with timesfm both in PyTorch and Flax/JAX backends.

🚀 Service construit par Johan Denoyer