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README.md
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license: apache-2.0
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---
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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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# 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arXiv has a previous outdated version of the paper and is still being updated with the latest version; please use the above link to access the latest version.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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