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NVIDIA has released the time series forecasting model Kumo Forecast (formerly NV-Tesseract Forecasting). The model uses MOMENT-1-large as its backbone, employing an encoder of approximately 340 million parameters plus a trainable forecasting head, with the encoder weights kept frozen. Its DARR mode retrieves patterns from historical data via k-nearest neighbors and fuses them with direct forecasting results; it also provides an interpretable framework that outputs lag and feature attributions by forecast step. The model is released under the Apache 2.0 license and supports input sequence lengths from 256 to 2048. There are currently no subsequent developments.
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- Source:Hugging Face
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Oct 21
Hugging FaceFirst-party
NVIDIA Kumo Forecast: An Interpretable Forecasting Model Combining Pretrained Time Series Representations and Historical Pattern Retrieval
NVIDIA Kumo Forecast (formerly NV-Tesseract Forecasting) is a multivariate time series forecasting model built on the MOMENT-1-large backbone, with an approximately 340-million-parameter encoder plus a trainable forecasting head, and the encoder weights are frozen. Its DARR mode retrieves patterns from historical data via k-nearest neighbors and fuses them with direct forecasts, and it also provides an interpretability framework that outputs lag and feature attributions by forecast step. The model is released under the Apache 2.0 license and supports input sequence lengths from 256 to 2048.