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title: README | |
emoji: π | |
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: [π€/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", | |
} | |
``` |