Time Series Forecasting
Transformers
PyTorch
Safetensors
time series
forecasting
classification
anomaly detection
imputation
pretrained models
foundation models
time-series
Instructions to use AutonLab/MOMENT-1-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AutonLab/MOMENT-1-large with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AutonLab/MOMENT-1-large", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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- **Repository:** https://github.com/moment-timeseries-foundation-model/
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- **Paper:** https://arxiv.org/abs/2402.03885
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- **Demo:** https://github.com/moment-timeseries-foundation-model/
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**APA:**
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Goswami, M., Szafer, K., Choudhry, A., Cai, Y., Li, S., & Dubrawski, A. (2024).
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MOMENT: A Family of Open Time-series Foundation Models.
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- **Repository:** https://github.com/moment-timeseries-foundation-model/ (Pre-training and research code coming out soon!)
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- **Paper:** https://arxiv.org/abs/2402.03885
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- **Demo:** https://github.com/moment-timeseries-foundation-model/
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**APA:**
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Goswami, M., Szafer, K., Choudhry, A., Cai, Y., Li, S., & Dubrawski, A. (2024).
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MOMENT: A Family of Open Time-series Foundation Models. In International Conference on Machine Learning. PMLR.
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