From the model card
Fields below are copied from the tags and counters on the HuggingFace repository Salesforce/moirai-1.0-R-base at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- Salesforce
- Pipeline tag
- time-series-forecasting
- Library
- Transformers
- Weight formats
- safetensors
- License tag
cc-by-nc-4.0— read the license file in the repo before relying on it- Papers cited
- arXiv:2402.02592
- Downloads (HF counter at last fetch)
- 405,106
- Likes (HF counter at last fetch)
- 32
- Model card
- https://huggingface.co/Salesforce/moirai-1.0-R-base
Use cases
- Cross-domain zero-shot forecasting on new time-series datasets
- Multivariate forecasting where series share common dynamics
- Evaluating generalist forecasting vs domain-specific baselines
- Automated forecasting in data pipelines without per-series tuning
- Probabilistic prediction with quantile outputs
Pros
- Multi-frequency support handles hourly through yearly series in one model
- Patch-based tokenization captures local temporal patterns efficiently
- Trained on diverse domains, reducing distribution mismatch for unseen series
- Published with full UNI2TS reproducibility code
Cons
- CC-BY-NC-4.0 license prohibits commercial use without separate licensing
- Multivariate support requires careful channel alignment across series
- Context window bounded; very long historical series require truncation or aggregation
- Quality on domain-specific series may lag fine-tuned models
Tags
transformerssafetensorstime seriesforecastingpretrained modelsfoundation modelstime series foundation modelstime-seriestime-series-forecastingarxiv:2402.02592license:cc-by-nc-4.0endpoints_compatibleregion:us