---
title: README
emoji: 🚀
colorFrom: gray
colorTo: red
sdk: static
pinned: false
---

## tasksource: 600+ dataset harmonization preprocessings with structured annotations for frictionless extreme multi-task learning and evaluation

Huggingface Datasets is a great library, but it lacks standardization, and datasets require preprocessing work to be used interchangeably.
`tasksource` automates this and facilitates reproducible multi-task learning scaling.

Each dataset is standardized to either `MultipleChoice`, `Classification`, or `TokenClassification` dataset with identical fields. We do not support generation tasks as they are addressed by [promptsource](https://github.com/bigscience-workshop/promptsource). All implemented preprocessings are in [tasks.py](https://github.com/sileod/tasksource/blob/main/src/tasksource/tasks.py) or [tasks.md](https://github.com/sileod/tasksource/blob/main/tasks.md). A preprocessing is a function that accepts a dataset and returns the standardized dataset. Preprocessing code is concise and human-readable.

GitHub: https://github.com/sileod/tasksource

### Installation and usage:
`pip install tasksource`
```python
from tasksource import list_tasks, load_task
df = list_tasks()

for id in df[df.task_type=="MultipleChoice"].id:
    dataset = load_task(id)
    # all yielded datasets can be used interchangeably
```

See supported 600+ tasks in [tasks.md](https://github.com/sileod/tasksource/blob/main/tasks.md) (+200 MultipleChoice tasks, +200 Classification tasks) and feel free to request a new task. Datasets are downloaded to `$HF_DATASETS_CACHE` (as any huggingface dataset), so be sure to have >100GB of space there.

### Pretrained model:

Text encoder pretrained on tasksource reached state-of-the-art results: [🤗/deberta-v3-base-tasksource-nli](https://hf.co/sileod/deberta-v3-base-tasksource-nli)

 ### Contact and citation
I can help you integrate tasksource in your experiments. `damien.sileo@inria.fr`

More details on this [article:](https://aclanthology.org/2024.lrec-main.1361/) 
```bib
@inproceedings{sileo-2024-tasksource-large,
    title = "tasksource: A Large Collection of {NLP} tasks with a Structured Dataset Preprocessing Framework",
    author = "Sileo, Damien",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1361",
    pages = "15655--15684",
}
```