metadata
language:
- en
tags:
- Machine Learning
- Research Papers
- Scientific Language Model
license: apache-2.0
MLRoBERTa (RoBERTa pretrained on ML Papers)
How to use:
from transformers import AutoTokenizer, AutoModel
tok = AutoTokenizer.from_pretrained('shrutisingh/MLRoBERTa')
model = AutoModel.from_pretrained('shrutisingh/MLRoBERTa')
Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.
Citation:
@inproceedings{singh2021compare,
title={COMPARE: a taxonomy and dataset of comparison discussions in peer reviews},
author={Singh, Shruti and Singh, Mayank and Goyal, Pawan},
booktitle={2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)},
pages={238--241},
year={2021},
organization={IEEE}
}