SalesforceAIResearch/uni2ts

Health v2 · maintenance only

Adoption not part of the score

1599 stars · 216 forks observed · 2026-09-27

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Uni2TS is a PyTorch library for unified pre-training, fine-tuning, inference, and evaluation of universal time series forecasting transformers like Moirai and Moirai-MoE. It provides a research framework with pre-trained model weights and benchmarking utilities.

Use cases

• forecast future values of time series with pre-trained transformer models
• fine-tune a universal time series foundation model on my own dataset
• run zero-shot time series forecasting without training a model
• evaluate forecasting models on Monash, LSF, and PF benchmarks
• pre-train a time series transformer at scale
• compare Moirai, TimesFM, Chronos, and VisionTS forecasters

When to choose

• you need state-of-the-art zero-shot or fine-tuned time series forecasting
• you are researching universal time series transformer architectures
• you want pre-trained Moirai model weights with PyTorch tooling

When to avoid

• you need simple classical forecasting methods like ARIMA or Prophet
• your project is not Python/PyTorch based
• you need production low-latency serving rather than research workflows

Facets

library · maturity active

machine-learning deep-learning llm-training time-series machine-learning deep-learning data-science python time-series-forecasting transformers pre-trained-models pre-training fine-tuning moirai pytorch

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