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YingLong 6M

Model directory
qcw2333/YingLong_6m

6M params | CC-BY-4.0 | Upstream checkpoint

YingLong 6M is the smallest checkpoint in the YingLong family, built for efficient zero-shot probabilistic forecasting. The official card and released code position it as a lightweight YingLong checkpoint, and at 6M parameters it is the most latency-friendly YingLong option in the catalog — the entry point to the family for anyone who wants foundation-model forecasting at the lowest possible serving footprint.

Architecturally it is a non-causal transformer forecaster: rather than the autoregressive decoder used by language-model-style forecasters, it relies on bidirectional attention over the input history and a multi-quantile output head, so a single forward pass emits calibrated quantiles instead of a sampled point trajectory. Like the rest of the released YingLong checkpoints, the official model card states it was pre-trained on 78B time points, which is what gives the family its broad zero-shot reach.

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Hugging Face · Weights & deployment

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Hugging Face provider mappings checked 2026-10-06. No Inference Provider mapping was listed for this checkpoint.

Model Classification

Family

YingLong

Type

time series foundation model

Pretrained time-series model for zero-shot or few-shot forecasting workloads.

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

forecastingquantile-forecastingzero-shothigh-throughput

Tags

yinglongprobabilisticlightweight

Specifications

Parameters
6M
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

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