v0.2.0 - Fine-tuning & Exogenous Variables

What's New

Fine-tuning Support

• FinetuneDataModule: PyTorch Lightning DataModule for training on custom HuggingFace datasets
• TotoForFinetuning: Lightning module with default configuration matching Toto's pretraining recipe
• Ready-to-use training script (finetune_toto.py) with YAML configuration
• Interactive tutorial notebook (finetuning_tutorial.ipynb)

Exogenous Variable Support

• Extended TotoBackbone to handle known future covariates (e.g., weather forecasts, scheduled events)
• Fusion module for combining target and exogenous variate embeddings with learnable labels
• Updated TotoForecaster to inject future exogenous values during autoregressive decoding

Evaluation & Benchmarking

• Custom evaluation on FEV datasets that are not included in Toto's pretraining corpus
• Evaluation scripts comparing zero-shot, fine-tuned, and fine-tuned with exogenous approaches
• Pre-computed results on 14 datasets (ENTSOE, EPF, Solar, UCI Air Quality, Rohlik)

Installation

pip install toto-ts==0.2.0

Full Changelog: v0.1.4...v0.2.0