Developed and integrated the Evolla protein-language generative model within the liguodongiot/transformers repository, focusing on decoding the molecular language of proteins to support advanced protein design workflows. The work involved enhancing model architecture, refining configuration options, and improving processing pipelines, all implemented using Python and leveraging deep learning frameworks such as PyTorch and transformers. Comprehensive testing was conducted to validate the model’s decoding and processing capabilities, and documentation was thoroughly updated to detail architecture, usage, and validation results. This feature established a robust foundation for future protein-language modeling, though no major bug fixes were addressed during this development period.