Text2Text Generation
Transformers
PyTorch
mt5
Inference Endpoints
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@@ -11,7 +11,7 @@ It is trained similarly to the [TRUE paper (Honovich et al, 2022)](https://arxiv
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  - Turkish
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- The input format for the model is: "premise: ARTICLE hypothesis: SUMMARY".
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  There is also a smaller (mT5-L) version of this model, as well as metrics trained for each of the other 5 dimensions described in the original paper.
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@@ -25,4 +25,6 @@ The full citation for the SEAHORSE paper is:
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  archivePrefix={arXiv},
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  primaryClass={cs.CL}
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  }
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- ```
 
 
 
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+ The input format for the model is: "premise: ARTICLE hypothesis: SUMMARY", where ARTICLE is the document being summarized and SUMMARY is the candidate summary.
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  There is also a smaller (mT5-L) version of this model, as well as metrics trained for each of the other 5 dimensions described in the original paper.
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  archivePrefix={arXiv},
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  primaryClass={cs.CL}
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  }
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+ ```
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+ Contact: seahorse-authors@google.com