metadata
license: apache-2.0
task_categories:
- text-classification
language:
- fr
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: test
path: test.jsonl
- config_name: raw
data_files:
- split: test
path: test.jsonl
- config_name: mteb_eval
data_files:
- split: test
path: mteb_eval.jsonl
Clustering HAL
This dataset was created by scrapping data from the HAL platform. Over 80,000 articles have been scrapped to keep their id, title and category.
It was originally used for the French version of MTEB, but it can also be used for various clustering or classification tasks.
Usage
To use this dataset, you can run the following code :
from datasets import load_dataset
dataset = load_dataset("lyon-nlp/clustering-hal-s2s", name="raw", split="test")
Citation
If you use this dataset in your work, please consider citing:
@misc{ciancone2024extending,
title={Extending the Massive Text Embedding Benchmark to French},
author={Mathieu Ciancone and Imene Kerboua and Marion Schaeffer and Wissam Siblini},
year={2024},
eprint={2405.20468},
archivePrefix={arXiv},
primaryClass={cs.CL}
}