t0-beta
t0-beta — Time-Series Forecasting
pretrained forecasting foundation model · test it on your series
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.
Serves
| Task | Answers |
|---|---|
| forecast | what happens next? |
Headline numbers
Provenance
| Publisher | The Forecasting Company ↗ |
| Weights | pretrained t0-beta · model.safetensors from HuggingFace |
| Input | (T,) series history (+ covariates) |
| License | Apache-2.0 (keep LICENSE and NOTICE) |
| Adapter | basemodels/t0-alpha/adapters/ · t0 |
| Source | huggingface.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.