metadata
language:
- en
dataset_info:
features:
- name: doc_id
dtype: string
- name: file_name
dtype: string
- name: key
dtype: string
- name: value
dtype: string
- name: text
dtype: string
splits:
- name: validation
num_bytes: 8498008
num_examples: 1102
download_size: 1381388
dataset_size: 8498008
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
task_categories:
- question-answering
- feature-extraction
This dataset is adapted from the paper Language Models Enable Simple Systems for Generating Structured Views of Heterogeneous Data Lakes. You can learn more about the data collection process there.
Please consider citing the following if you use this task in your work:
@article{arora2024simple,
title={Simple linear attention language models balance the recall-throughput tradeoff},
author={Arora, Simran and Eyuboglu, Sabri and Zhang, Michael and Timalsina, Aman and Alberti, Silas and Zinsley, Dylan and Zou, James and Rudra, Atri and Ré, Christopher},
journal={arXiv:2402.18668},
year={2024}
}