Update README.md

README.md

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 # AbMAP: Antibody Mutagenesis-Augmented Processing
 *This repository is a work in progress.*
 
-This repository contains code and pre-trained model checkpoints for AbMAP, a Protein Language Model (PLM) customized for antibodies as featured in **Learning the Language of Antibody Hypervariability** (_Singh, Im et al. 2023_) [Link](https://www.biorxiv.org/content/10.1101/2023.04.26.538476v1). AbMAP leverages information from foundational PLMs as well as antibody structure and function, offering a multi-functional tool useful for predicting structure, functional properties, and analyzing B-cell repertoires.
+This repository contains code and pre-trained model checkpoints for AbMAP, a Protein Language Model (PLM) customized for antibodies as featured in **Learning the Language of Antibody Hypervariability** (_Singh, Im et al. 2023_) [Link](https://www.biorxiv.org/content/10.1101/2023.04.26.538476). AbMAP leverages information from foundational PLMs as well as antibody structure and function, offering a multi-functional tool useful for predicting structure, functional properties, and analyzing B-cell repertoires.
 
 ### Installation
 ```bash
@@ -10,17 +10,16 @@ pip install git+https://github.com/rs239/ablm.git  # the live main branch
 ```
 
 ### Usage:
-After installation, AbMAP can be easily imported into your python projects or run from the command line. Please see [examples/demo.ipynb](examples/demo.ipynb/) for common use cases. Instructions for running via CLI are below.
+After installation, AbMAP can be easily imported into your python projects or run from the command line. Please see [examples/demo_detailed.ipynb](examples/demo_detailed.ipynb/) for common use cases. Instructions for running via CLI are below.
+
+## Command Line Usage *Instructions In Progress*
 
-## Command Line Usage
 ### Augment
-*Instructions In Progress*
 Given a sequence, generate a foundational PLM embedding augmented with in-silico mutagenesis and CDR isolation.
 ### Train
 Given a dataset of labeled pairs of sequences and their augmented embeddings, train the AbMAP model on downstream prediction tasks.
 ### Embed
 Given fasta sequences and a pre-trained AbMAP model, generate their AbMAP embeddings (fixed or variable).
 
-## Reference
-<a id="1">[1]</a>
-Madeira, Fábio, et al. "Search and sequence analysis tools services from EMBL-EBI in 2022." Nucleic acids research 50.W1 (2022): W276-W279. (Transeq)
+Please provide feedback on the issues page or by opening a pull request. If AbMAP is useful in your work, please consider citing our [bioRxiv preprint](https://www.biorxiv.org/content/10.1101/2023.04.26.538476). 
+