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README.md

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 # ProtBert-BFD-SS3
 
-Pretrained model on protein sequences using a masked language modeling (MLM) objective. The model makes a per-residue (per-token) prediction of protein secondary structure (3-state accuracy), i.e. H (helix), E (strand) or C (coil). The model was developed by Ahmed Elnaggar et al. and more information can be found on the GitHub repository and in the accompanying paper. This repository is a fork of their HuggingFace repository. This model is trained on uppercase amino acids: it only works with capital letter amino acids.
+Pretrained model on protein sequences using a masked language modeling (MLM) objective. The model makes a per-residue (per-token) prediction of protein secondary structure (3-state accuracy), i.e. H (helix), E (strand) or C (coil). The model was developed by Ahmed Elnaggar et al. and more information can be found on the [GitHub repository](https://github.com/agemagician/ProtTrans) and in the [accompanying paper](https://ieeexplore.ieee.org/document/9477085). This repository is a fork of their [HuggingFace repository](https://huggingface.co/Rostlab/prot_bert_bfd_ss3).
+This model is trained on uppercase amino acids: it only works with capital letter amino acids.
 
 ## Model description
 The model has no auxiliary tasks like BERT's next-sentence prediction. Only the main objective - MLM - was used.