---
license: cc
---

## About

This repository provides model weights to run load forecasting models trained on ComStock datasets. The companion dataset repository is [this](https://huggingface.co/datasets/APPFL/Illinois_load_datasets). The model definitions are present in the `models` directory. The corresponding trained model weights are present in the `weights` directory. The corresponding model keyword arguments (as a function of a provided `lookback` and `lookahead`) can be imported from the file `model_kwargs.py`.

Note that `lookback` is denoted by `L` and `lookahead` by `T` in the weights directory. We provide weights for the following `(L,T)` pairs: `(96,4)`, `(96,48)`, and `(96,96)`.

## Data

When using the companion [dataset](https://huggingface.co/datasets/APPFL/Illinois_load_datasets), the following points must be noted (see the dataset for more information on configuring the data loaders):

- All models accept normalized inputs and produce normalized outputs, i.e. set `normalize = True` when generating the datasets.
- For Transformer, Autoformer, Informer, and TimesNet set `transformer = True`, while for LSTM and LSTNet, set `transformer = False`.

## Credits

Some model definitions have been adapted from the code provided in the [TSLib Library](https://github.com/thuml/Time-Series-Library).