{
  "slug": "gift-eval-2024",
  "title": "GIFT-Eval: General Time Series Forecasting Model Evaluation",
  "canonical_source_url": "https://huggingface.co/datasets/Salesforce/GiftEval",
  "official_code_url": "https://github.com/SalesforceAIResearch/gift-eval",
  "official_leaderboard_url": "https://huggingface.co/spaces/Salesforce/GIFT-Eval",
  "paper_url": "https://arxiv.org/abs/2410.10393",
  "dataset_type": "general-purpose time-series forecasting benchmark and non-leaking pretraining corpus",
  "temporal_structure": "heterogeneous forecasting tasks across domains, frequencies, variate counts, and prediction lengths",
  "actions_or_interventions": "none; passive forecasting benchmark",
  "suitability_note": "standard broad TSFM evaluation surface used by Toto and Toto 2.0; useful for general zero-shot comparison but not a high-dimensional observability benchmark",
  "license_note": "Hugging Face release is marked as research-purpose support for the GIFT-Eval paper; check the component datasets for downstream use constraints",
  "versioning_note": "public summaries describe the train/test component with slightly different dataset counts, so exact counts should be tied to a specific artifact or paper version",
  "reported_scale": {
    "time_series": 144000,
    "data_points": "roughly 177 million on the Hugging Face card; some papers report nearby values depending on version/counting",
    "configurations": 97
  },
  "created": "2026-05-15",
  "updated": "2026-05-15"
}