nv-tesseract-forecasting

NV-Tesseract-Forecasting Overview Description: NVIDIA NV-Tesseract-Forecasting provides forecasting functionality via NVIDIA's novel DARR (Domain-Aware Representation and Retrieval) which is a context-enhanced forecasting mode that combines direct model predictions with pattern retrieval from historical data. The model leverages MOMENT encoders with a trainable forecasting head for accurate long-horizon time series predictions. This model is for research and development only. License/Terms of Use: GOVERNING TERMS: Use of this model is governed by the Apache-2.0 License Deployment Geography: Global Use Case: Companies, organizations, research hubs looking to do long/short-horizon forecasting on temporal data. Release Date: HuggingFace 04/07/2026 via https://huggingface.co/nvidia/nv-tesseract-forecasting Reference(s): Memory-Augmented Forecasting: Scalability and Generalization Across Temporal Domains Beyond MAE: Measuring Forecast Reliability with Temporal Dependence-Aware Error (TDE) MOMENT: A Family of Open Time-series Foundation Models TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting Model Architecture: Architecture Type:** MOMENT-based Transformer with trainable forecasting head Network Architecture:** Transformer Encoder (MOMENT-1-large backbone) Number of model parameters:** ~340 million (base encoder) + trainable forecasting head The NV-Tesseract-Forecasting is a Transformer-based model for time series forecasting. It uses MOMENT encoders with frozen encoder and embedder weights, while training only the forecasting head. The model supports DARR (Domain-Aware Representation and Retrieval) mode, which enhances predictions by combining direct forecasts with kNN-based pattern retrieval from historical context data. Input: Input Type(s):** Tabular numeric Input Format(s):** Tabular Pandas DataFrame or CSV/JSON Input Parameters:** 2D Other Properties Related to Input:** Pre-Processing Needed Forecasting: Contains timestamp column a