moirai 1.0 R large EU AI Act Compliance Profile

Moirai-1.0-R-Large

Moirai, the Masked Encoder-based Universal Time Series Forecasting Transformer is a Large Time Series Model pre-trained on LOTSA data. For more details on the Moirai architecture, training, and results, please refer to the paper.

Usage

To perform inference with Moirai, install the uni2ts library from our GitHub repo.

1. Clone repository:

git clone https://github.com/SalesforceAIResearch/uni2ts.git
cd uni2ts

1. Create virtual environment:

virtualenv venv
. venv/bin/activate

1. Build from source:

pip install -e '.[notebook]'

1. Create a .env file:

touch .env

A simple example to get started:

import torch
import matplotlib.pyplot as plt
import pandas as pd
from gluonts.dataset.pandas import PandasDataset
from gluonts.dataset.split import split

from uni2ts.eval_util.plot import plot_single
from uni2ts.model.moirai import MoiraiForecast, MoiraiModule


SIZE = "small"  # model size: choose from {'small', 'base', 'large'}
PDT = 20  # prediction length: any positive integer
CTX = 200  # context length: any positive integer
PSZ = "auto"  # patch size: choose from {"auto", 8, 16, 32, 64, 128}
BSZ = 32

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