| pipeline_tag: time-series-forecasting | |
| tags: | |
| - model_hub_mixin | |
| - pytorch_model_hub_mixin | |
| - time series foundation models | |
| - pretrained models | |
| - time series | |
| Moirai is a large pre-trained Time Series Model based on the Masked Encoder architecture. It is a universal time series forecasting model capable of addressing diverse forecasting tasks across multiple domains, frequencies, and variables in a zero-shot manner. | |
| This is a version of [Moirai small](https://huggingface.co/Salesforce/moirai-1.1-R-small) trained by Faculty AI. It was pre-trained on the [LOTSA data](https://huggingface.co/datasets/Salesforce/lotsa_data) using the [codebase](https://github.com/SalesforceAIResearch/uni2ts/tree/main/cli/conf/pretrain) provided by Woo et al. (2024). Both the dataset and codebase are licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). For more details on the model architecture, training, and results, please refer to the [paper](https://arxiv.org/abs/2402.02592). | |
| ### Usage | |
| Please follow the [Installation](https://github.com/SalesforceAIResearch/uni2ts?tab=readme-ov-file#%EF%B8%8F-installation) instructions and [Getting Started](https://github.com/SalesforceAIResearch/uni2ts?tab=readme-ov-file#-getting-started) section provided in the uni2ts repo. To use the model trained by Faculty AI simply use `FacultyAI/moirai-small` when fetching the model weights. | |
| ``` | |
| model = MoiraiForecast( | |
| module=MoiraiModule.from_pretrained("FacultyAI/moirai-small"), | |
| ... | |
| ) | |
| ``` | |
| References | |
| ```markdown | |
| Woo, G., Liu, C., Kumar, A., Xiong, C., Savarese, S., & Sahoo, D. (2024). Unified Training of Universal Time Series Forecasting Transformers. arXiv preprint arXiv:2402.02592. | |
| ``` | |