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
Add a pipeline tag for time series forecasting
Browse files
README.md
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- pretrained models
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- foundation models
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- time-series
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---
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# MOMENT-Large
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@@ -136,4 +137,4 @@ If you use MOMENT please cite our paper:
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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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- pretrained models
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- foundation models
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- time-series
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pipeline_tag: time-series-forecasting
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---
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# MOMENT-Large
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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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