Update README.md

README.md

@@ -4,6 +4,7 @@ pipeline_tag: fill-mask
 language: en
 datasets:
 - OpenSubtitles
+library_name: transformers
 ---
 ## Model description
 This model is based on [An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification](https://arxiv.org/abs/2210.05529). Ilias Chalkidis, Xiang Dai, Manos Fergadiotis, Prodromos Malakasiotis, and Desmond Elliott. 2022. arXiv:2210.05529 (Preprint).
@@ -11,4 +12,4 @@ This model is based on [An Exploration of Hierarchical Attention Transformers fo
 Initial weights were taken from [google/bert_uncased_L-8_H-256_A-4](https://huggingface.co/google/bert_uncased_L-8_H-256_A-4).
 Model was additionally pretrained for 20_000 steps on 5m lines of text from english version of [OpenSubtitles](http://www.opensubtitles.org/) dataset. 
 
-Maximum input length is 512 tokens that is enoungh to encode dialog with few previous utterances (average sentence length per utterance in SWDA, MAPTASK, MRDA, BT_OASIS, FRAMES, AMI, DSTC3 is less than 11 tokens). 
+Maximum input length is 512 tokens that is enoungh to encode dialog with few previous utterances (average sentence length per utterance in SWDA, MAPTASK, MRDA, BT_OASIS, FRAMES, AMI, DSTC3 is less than 11 tokens).