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t0-beta

t0-beta — Time-Series Forecasting

pretrained forecasting foundation model · test it on your series

forecastForecastingApache-2.0 (keep LICENSE and NOTICE)

Choose this to forecast your own time series without training. Inference-only.

Run it

$ pip install pfnstudio
$ pfnstudio run t0-beta --input <your file>

# ex:
$ pfnstudio run t0-beta --input sample

# download it without running · its tasks, inputs, license and digest
$ pfnstudio pull t0-beta
$ pfnstudio show t0-beta

# models loaded now · delete it from this machine
$ pfnstudio ps
$ pfnstudio rm t0-beta

Python 3.10+. The first run downloads the model's adapter, asks before installing PyTorch and the model's own packages (-y installs without asking) and pulls the pretrained weights from Hugging Face. --input sample runs the sample input pfnstudio ships and prints its path: copy it, put your data in, and pass it as <your file>. Later runs reuse the cache.

Continue pretraining →

Serves

TaskAnswers
forecastwhat happens next?

Headline numbers

Params
~255.6M
Output
Quantiles
multi-horizon

Provenance

PublisherThe Forecasting Company ↗
Weightspretrained t0-beta · model.safetensors from HuggingFace
Input(T,) series history (+ covariates)
LicenseApache-2.0 (keep LICENSE and NOTICE)
Adapterbasemodels/t0-alpha/adapters/ · t0
Sourcehuggingface.co/theforecastingcompany/t0-beta ↗

Readme

A ready-to-use forecasting model you can point at your own history — it predicts the next weeks of sales, demand or any metric, with a range, without training a model.

t0-beta (The Forecasting Company) is a zero-shot time-series forecasting transformer (~255.6M parameters). It reads a series' history in patches and returns quantile forecasts for the next steps. This listing installs the real pretrained weights as an inference-only base model: the checkpoint is pulled from HuggingFace (theforecastingcompany/t0-beta) at run time and served through the upstream tfc-t0 package.