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license: apache-2.0 |
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tags: |
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- time series |
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- forecasting |
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- pretrained models |
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- foundation models |
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- time series foundation models |
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--- |
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# Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting |
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![lag-llama-architecture](images/lagllama.webp) |
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Lag-Llama is the <b>first open-source foundation model for time series forecasting</b>! |
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Twitter Thread: https://twitter.com. |
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HuggingFace: {} |
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Colab Demo: {} |
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Paper: {Not arxiv}. |
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arXiv has a previous outdated version of the paper and is still being updated with the latest version; please use the above link to access the latest version. |
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This repository houses the Lag-Llama architecture. |
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<b>Current Features:</b> |
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1. <b>Zero-shot forecasting</b> on a dataset of <b>any frequency</b> for <b>any prediction length</b>, using the Colab Demo. |
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Coming Soon: |
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1. An <b>online gradio demo</b> to upload time series and get zero-shot predictions for |
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1. Features for <b>finetuning</b> the foundation model |
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2. Features for <b>pretraining</b> Lag-Llama on your own large-scale data |
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3. Scripts to <b>reproduce</b> all results in the paper. |
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