Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well as synthetic data generated using Gaussian processes.
Features
- The models in this repository are based on the T5 architecture
- Documentation available
- Zero-Shot Results
- The recommended way of using Chronos for production use cases is through AutoGluon
- Forecasting
- Examples available
- Pretraining, fine-tuning and evaluation
Categories
Machine LearningLicense
Apache License V2.0Follow Chronos Forecasting
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