feat: add T0Model foundation model

CHANGELOG.md

@@ -11,6 +11,7 @@ but cannot always guarantee backwards compatibility. Changes that may **break co
 
 **Improved**
 
+- 🚀 Added new forecasting model `T0Model` : The Forecasting Company's open-weights ~100M-parameter foundation model for zero-shot forecasting. It supports univariate, multivariate, and multiple time series as well as past and future covariates, and can output deterministic or probabilistic forecasts. It can be used zero-shot or fine-tuned (full or partial) via `enable_finetuning`. [#3142](https://github.com/unit8co/darts/pull/3142) by [Geoffrey Négiar](https://github.com/GeoffNN).
 - Added support for per-timestep (non-aggregated) encoder and decoder variable importances in `TFTExplainer`, exposed as `TimeSeries` via `TFTExplainabilityResult.get_encoder_importance_over_time()` and `get_decoder_importance_over_time()`. [#3170](https://github.com/unit8co/darts/pull/3170) by [exactml](https://github.com/exactml).
 - Calling `TFTModel.fit_from_dataset()` on a dataset that does not have future covariates now raises an informative exception. [#3149](https://github.com/unit8co/darts/pull/3149) by [YOON KIWOONG](https://github.com/kiwoongyoon).
 - 🔴 Percentage and range-based metrics (`ape`, `mape`, `sape`, `smape`, `wmape`, `ope`, `arre`, `marre`, `coefficient_of_variation`) no longer raise a hard `ValueError` when the denominator is exactly zero. A new `zero_division` parameter controls the behavior: [#3122](https://github.com/unit8co/darts/pull/3122) by [Mahimn](https://github.com/mahimn01).

INSTALL.md

@@ -21,6 +21,7 @@ Some models have additional dependencies that are not included in the `all` inst
 |-----------------------|-----------------------|
 | `NeuralForecastModel` | neuralforecast>=3.0.0 |
 | `TiRexModel`          | tirex-ts>=1.4.0       |
+| `T0Model`             | tfc-t0>=0.2.2         |
 
 
 ## From conda-forge
@@ -52,6 +53,7 @@ Some models have dependencies not available on conda-forge. To use them, you nee
 | Model                 | Dependencies          |
 |-----------------------|-----------------------|
 | `TiRexModel`          | tirex-ts>=1.4.0       |
+| `T0Model`             | tfc-t0>=0.2.2         |
 
 
 ## Other Information

README.md

@@ -280,6 +280,7 @@ Here's a breakdown of the forecasting models currently implemented in Darts. Our
 | [TimesFM2p5Model](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.timesfm2p5_model.html#darts.models.forecasting.timesfm2p5_model.TimesFM2p5Model)                                                                                                                        | [TimesFM 1.0 paper](https://arxiv.org/abs/2310.10688), [Google blog post](https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting)                                                               | ✅ ✅                                                          | 🔴 🔴 🔴                                                                 | ✅ ✅                                                                      | ✅                                         |
 | [TiRexModel](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.tirex_model.html#darts.models.forecasting.tirex_model.TiRexModel)                                                                                                                                            | [TiRex paper](https://arxiv.org/abs/2505.23719), [TiRex GitHub](https://github.com/NX-AI/tirex)                                                                                                                                   | ✅ ✅                                                          | 🔴 🔴 🔴                                                                 | ✅ ✅                                                                      | ✅                                         |
 | [PatchTSTFMModel](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.patchtst_fm_model.html#darts.models.forecasting.patchtst_fm_model.PatchTSTFMModel)                                                                                                                      | [PatchTST-FM paper](https://arxiv.org/abs/2602.06909), [PatchTST-FM GitHub](https://github.com/ibm-granite/granite-tsfm)                                                                                                          | ✅ ✅                                                          | 🔴 🔴 🔴                                                                 | ✅ ✅                                                                      | ✅                                         |
+| [T0Model](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.t0_model.html#darts.models.forecasting.t0_model.T0Model)                                                                                                                                                       | [T0 model card](https://huggingface.co/theforecastingcompany/t0-alpha), [tfc-t0 GitHub](https://github.com/theforecastingcompany/tfc-t0)                                                                                          | ✅ ✅                                                          | ✅ ✅ 🔴                                                                 | ✅ ✅                                                                      | ✅                                         |
 | **Ensemble Models**<br/>([GlobalForecastingModel](https://unit8co.github.io/darts/userguide/covariates.html#global-forecasting-models-gfms)): Model support is dependent on ensembled forecasting models and the ensemble model itself                                                           |                                                                                                                                                                                                                                   |                                                              |                                                                          |                                                                          |                                           |
 | [NaiveEnsembleModel](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.naive_ensemble_model.html#darts.models.forecasting.naive_ensemble_model.NaiveEnsembleModel)                                                                                                          |                                                                                                                                                                                                                                   | ✅ ✅                                                          | ✅ ✅ ✅                                                                    | ✅ ✅                                                                      | ✅                                         |
 | [RegressionEnsembleModel](https://unit8co.github.io/darts/generated_api/darts.models.forecasting.regression_ensemble_model.html#darts.models.forecasting.regression_ensemble_model.RegressionEnsembleModel)                                                                                      |                                                                                                                                                                                                                                   | ✅ ✅                                                          | ✅ ✅ ✅                                                                    | ✅ ✅                                                                      | ✅                                         |

darts/models/__init__.py

@@ -106,6 +106,7 @@
         SKLearnClassifierModel as SKLearnClassifierModel,
     )
     from darts.models.forecasting.sklearn_model import SKLearnModel as SKLearnModel
+    from darts.models.forecasting.t0_model import T0Model as T0Model
     from darts.models.forecasting.tcn_model import TCNModel as TCNModel
     from darts.models.forecasting.tft_model import TFTModel as TFTModel
     from darts.models.forecasting.theta import FourTheta as FourTheta
@@ -191,6 +192,7 @@
     "PatchTSTFMModel": ("darts.models.forecasting.patchtst_fm_model", "(Py)Torch"),
     "TimesFM2p5Model": ("darts.models.forecasting.timesfm2p5_model", "(Py)Torch"),
     "TiRexModel": ("darts.models.forecasting.tirex_model", "(Py)Torch and/or TiRex-TS"),
+    "T0Model": ("darts.models.forecasting.t0_model", "(Py)Torch and/or tfc-t0"),
     # --- Forecasting: NeuralForecast ---
     "NeuralForecastModel": ("darts.models.forecasting.nf_model", "NeuralForecast"),
     # --- Forecasting: Prophet ---

darts/models/forecasting/__init__.py

@@ -59,6 +59,7 @@
     - :class:`~darts.models.forecasting.timesfm2p5_model.TimesFM2p5Model`
     - :class:`~darts.models.forecasting.tirex_model.TiRexModel`
     - :class:`~darts.models.forecasting.patchtst_fm_model.PatchTSTFMModel`
+    - :class:`~darts.models.forecasting.t0_model.T0Model`
 Ensemble Models (`GlobalForecastingModel <https://unit8co.github.io/darts/userguide/covariates.html#global-forecasting-models-gfms>`__)
     - :class:`~darts.models.forecasting.naive_ensemble_model.NaiveEnsembleModel`
     - :class:`~darts.models.forecasting.regression_ensemble_model.RegressionEnsembleModel`