Datasets › TSFM-ScalingLaws-Dataset
TSFM-ScalingLaws-Dataset
TSFM-ScalingLaws-Dataset
This is the dataset for the paper Towards Neural Scaling Laws for Time Series Foundation Models.
We selected some high-quality (SNR > 20), domain-balanced, and low-redundancy data from Lotsa and UTS datasets for TSFM pre-training. These datasets contain three sizes: 16B, 1B, 100M, and 10M.
Code: https://github.com/Qingrenn/TSFM-ScalingLaws
Well-trained models: https://huggingface.co/PeacefulData/TSFM-ScalingLaws-Checkpoints
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.
Dataset loaders archive 2025-07-28
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Tasks archive 2025-07-28
License archive 2025-07-28
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Modalities archive 2025-07-28
Languages archive 2025-07-28
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Variants archive 2025-07-28
- TSFM-ScalingLaws-Dataset
1 variant name, as the archive lists them.
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