YingLong 300M
Model directoryqcw2333/YingLong_300m300M params | CC-BY-4.0 | Upstream checkpoint
YingLong 300M is the largest checkpoint in the YingLong family, offering the highest forecast quality at the cost of increased latency. The official paper frames it as the top-capacity YingLong release for zero-shot forecasting, the ceiling of the family rather than its cheapest tier.
The broader family continues to use direct quantile-style probabilistic outputs rather than a language-model-style decoder, and YingLong 300M keeps that non-causal transformer design: bidirectional attention over the input history feeding a multi-quantile output head, so calibrated prediction intervals come straight out of a single forward pass. The official model card states the released YingLong checkpoints were pre-trained on 78B time points, the same corpus that gives the family its zero-shot reach across domains.
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Model Classification
Family
YingLong
Type
time series foundation model
Pretrained time-series model for zero-shot or few-shot forecasting workloads.
Resources
Training Data
Official model card states that the released YingLong checkpoints were pre-trained on 78B time points.
Recommended For
- • Dense probabilistic forecasting with fine-grained quantile coverage
- • Workloads that need richer distribution coverage than standard low-count quantile sets
Strengths
- • Quantile-focused output head provides unusually dense probabilistic coverage
- • Clear parameter-size ladder from 6M to 300M for cost-accuracy tradeoffs
Limitations
- • Newer family with less public benchmark coverage than the most established TSFMs
- • Dense quantile output increases per-token cost compared to point-forecast-only models
Capabilities
Tags
Specifications
- Parameters
- 300M
- Architecture
- non-causal transformer forecaster with multi-quantile output head
- Context length
- n/a
- Max context
- n/a
- Minimum history
- n/a
- Recommended history
- n/a
- Input step
- n/a
- Required target series
- 1
- Temperature
- Ignored
- Top P
- Ignored
- Max output
- n/a
- License
- CC-BY-4.0