

# 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](https://arxiv.org/abs/2204.06674).

# 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](https://github.com/acolas1/GAP_COLING2022).
{"language": ["en"], "license": "apache-2.0", "tags": ["NLG", "pytorch", "transformers", "BART", "Graph-to-Text", "Knowledge Graph"], "datasets": ["WebNLG", "EventNarrative"]}
transformers NLG pytorch BART Graph-to-Text Knowledge Graph en dataset:WebNLG dataset:EventNarrative arxiv:2204.06674 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #NLG #pytorch #BART #Graph-to-Text #Knowledge Graph #en #dataset-WebNLG #dataset-EventNarrative #arxiv-2204.06674 #license-apache-2.0 #endpoints_compatible #region-us 



# 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.

If you found this model useful, please consider citing our paper:


# GitHub repo
Please see our GitHub here.
# 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.

If you found this model useful, please consider citing our paper: # GitHub repo
Please see our GitHub here.
TAGS
#transformers #NLG #pytorch #BART #Graph-to-Text #Knowledge Graph #en #dataset-WebNLG #dataset-EventNarrative #arxiv-2204.06674 #license-apache-2.0 #endpoints_compatible #region-us 
 # 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.

If you found this model useful, please consider citing our paper: # GitHub repo
Please see our GitHub here.
TAGS
#transformers #NLG #pytorch #BART #Graph-to-Text #Knowledge Graph #en #dataset-WebNLG #dataset-EventNarrative #arxiv-2204.06674 #license-apache-2.0 #endpoints_compatible #region-us 
# 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.

If you found this model useful, please consider citing our paper:# GitHub repo
Please see our GitHub here.