Training mRNA Language Models Across 25 Species for $165
Hugging Face
OpenMed built an end-to-end protein engineering pipeline combining structure prediction, sequence design, and codon optimization across 25 species for $165 in compute costs. CodonRoBERTa-large-v2 achieved a perplexity of 4.10 and CAI correlation of 0.40, outperforming ModernBERT by 6x, with four production models trained in 55 GPU-hours. The system enables researchers to move from a protein concept to synthesis-ready DNA sequences by applying transformer models trained specifically on biological codon statistics rather than natural language patterns.