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README.md
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@@ -136,4 +136,27 @@ features_mean = np.mean(features[0], axis=0)
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# features_mean = np.mean(features[0], axis=0)
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# #features_max = np.max(features[0], axis=0)
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```
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# features_mean = np.mean(features[0], axis=0)
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# #features_max = np.max(features[0], axis=0)
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```
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### BibTeX entry and citation info
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Please cite the [reference paper](https://aclanthology.org/2020.findings-emnlp.148/) if you use this model.
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```bibtex
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@inproceedings{barbieri-etal-2020-tweeteval,
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title = "{T}weet{E}val: Unified Benchmark and Comparative Evaluation for Tweet Classification",
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author = "Barbieri, Francesco and
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Camacho-Collados, Jose and
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Espinosa Anke, Luis and
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Neves, Leonardo",
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
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month = nov,
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year = "2020",
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address = "Online",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2020.findings-emnlp.148",
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doi = "10.18653/v1/2020.findings-emnlp.148",
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pages = "1644--1650"
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}
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```
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