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Graph-Aware-PretrainedLM
DSR-UF/Graph-Aware-PretrainedLM
Graph-Aware-PretrainedLM is a machine learning model from DSR-UF. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
We release our best performing models for the WebNLG and EventNarrative datasets from the paper GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation. Our model is intended to be used on k…
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Updated Mar 16, 2023
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671 MB
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Mar 15, 2023
- Updated
- Mar 16, 2023
- SHA
- 8d391000
Datasets
Model card
From the Hugging Face model README
Model Description
We release our best performing models for the WebNLG and EventNarrative datasets from the paper GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation. Our model is intended to be used on knowledge graphs in order to narrate their contents, giving a verbalization of the structured data.
Paper
Please see our paper here.
Citation
If you found this model useful, please consider citing our paper:
@inproceedings{colas-etal-2022-gap,
title = "{GAP}: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation",
author = "Colas, Anthony and
Alvandipour, Mehrdad and
Wang, Daisy Zhe",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.506",
pages = "5755--5769"
}
GitHub repo
Please see our GitHub here.
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Mar 15, 2023
- Updated
- Mar 16, 2023