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README
Toto-2.0-22m (int8 ONNX)
int8 ONNX export of Datadog/Toto-2.0-22m (Apache-2.0), quantized as: blocked weight-only QInt8 (opset-21 blocked DequantizeLinear, 16-row blocks); output head kept fp32. Requires onnxruntime >= 1.20; untested under onnxruntime-web.
Unofficial export, not affiliated with or endorsed by the model authors.
Contract
| input | dtype | shape | notes |
|---|---|---|---|
context | float32 | ['variates', 2048] | NaN |
series_ids | int64 | ['variates'] | variates sharing an id are forecast jointly through variate-axis attention; distinct ids = independent |
Output quantiles: float32 ['variates', 96, 9]. Quantile levels: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9].
One parallel pass to 96 steps. Left-pad short series with NaN (missing-aware). Median is level index 4.
Contributors
6 commits
Similar repos
Linked in READMEs
0
stars
6
commits
2
linked in READMEs
Sep 1, 2026
updated
README
Toto-2.0-22m (int8 ONNX)
int8 ONNX export of Datadog/Toto-2.0-22m (Apache-2.0), quantized as: blocked weight-only QInt8 (opset-21 blocked DequantizeLinear, 16-row blocks); output head kept fp32. Requires onnxruntime >= 1.20; untested under onnxruntime-web.
Unofficial export, not affiliated with or endorsed by the model authors.
Contract
| input | dtype | shape | notes |
|---|---|---|---|
context | float32 | ['variates', 2048] | NaN |
series_ids | int64 | ['variates'] | variates sharing an id are forecast jointly through variate-axis attention; distinct ids = independent |
Output quantiles: float32 ['variates', 96, 9]. Quantile levels: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9].
One parallel pass to 96 steps. Left-pad short series with NaN (missing-aware). Median is level index 4.
Similar repos
Linked in READMEs
Contributors
6 commits