Update README.md

README.md

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 # Naive/Memory Heavy Chain Classifier
 
-This repository provides a transformer-based classifier for distinguishing between **naive and memory B-cell** receptor heavy chain sequences. It leverages adapters integrated into pre-trained language models for efficient fine-tuning. The model is fine-tuned from [HeavyBERTa](https://huggingface.co/leaBroe/HeavyBERTa), a protein language model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) architecture, pre-trained on a large corpus of unpaired heavy chain sequences from the [OAS](https://opig.stats.ox.ac.uk/webapps/oas/) database.
+This repository provides a transformer-based classifier for distinguishing between **naive and memory B-cell** receptor heavy chain sequences. It uses adapters integrated into pre-trained language models for efficient fine-tuning. The model is fine-tuned from [HeavyBERTa](https://huggingface.co/leaBroe/HeavyBERTa), a protein language model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) architecture, pre-trained on a large corpus of unpaired heavy chain sequences from the [OAS](https://opig.stats.ox.ac.uk/webapps/oas/) database.
 An equivalent classification model for light chains can be found [here](https://huggingface.co/leaBroe/LightGPT_naive_mem_cls).  
 
 For more information of how to use this model, please visit our Github [repository](https://github.com/ibmm-unibe-ch/Heavy2Light/blob/main/naive_memory_cls/README.md).