The Final Hybrid: Merging Two Monolingual Language Models Through Genetic Tensor Expansion Without Retraining

This work documents the successful hybridization of two monolingual language models without retraining. Each model was t This work documents the successful hybridization of two monolingual language models without retraining. Each model was trained on a different single language. The method uses zero-padding expansion for 2D tensors and repetition for 1D tensors. RAM is limited to 4GB. The tokenizer formats differ (tokenizer.json vs vocab.json) and require manual alignment before hybridization. Results confirm that both original languages are preserved, no single model dominates, and emergent cross-lingual capabilities are observed. The hybrid model can evolve further through additional hybridizations. Code is available on GitHub: https://github.com/mouad-tarif/Monolingual-Hybridization --- Correspondence Policy (Strictly Enforced) **No personal email addresses (Gmail, Yahoo, Outlook, ProtonMail, etc.) will receive any response.** For academic or research collaboration:1. Use your **institutional email** (.edu, .ac.*, or verified research domain)2. Or contact through **GitHub** (for code-related issues) **Why this policy?**- To protect research time from spam, predatory journals, and automated bots.- To ensure serious academic discourse only. **Note on the author's email:** The author uses `[email protected]`, which is a personal email provided by **mail.ru** (a legitimate email service). This is a **personal exception** based on the author's long-term usage and research history. It does not imply acceptance of other personal email domains. Any other personal email (Gmail, Yahoo, Outlook, ProtonMail, etc.) will be ignored permanently. **Violations will be ignored permanently.**