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README.md

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-license: apache-2.0
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+# MALM: Modular Adapter-based Language Model  
+📄 [Read the full paper (MALM.pdf)](./MALM.pdf)  
+📝 Author: **Hilal Limo (Independent Researcher, 15)**  
+📜 License: [Apache-2.0](./LICENSE)  
+
+---
+
+## Overview
+This repository contains the research paper **MALM: Modular Adapter-based Language Model**, which introduces a lightweight and scalable framework for multilingual AI.  
+Instead of relying on massive monolithic models, MALM separates **reasoning** and **translation** into two modular parts:
+
+- **Core Language Model (CLM):** A compact, English-focused reasoning engine.  
+- **Specialized Translation Adapters (STAs):** Lightweight, swappable neural machine translation models.  
+- **Orchestration Layer:** Connects the pieces, parsing delegation tokens (e.g. `<to:de> ... </to>`) and routing requests to the right adapter.  
+
+This design drastically reduces compute cost, makes it easier to add new languages, and is especially useful for **small models**, edge devices, and research settings.
+
+---
+
+## Why MALM?
+- 🚀 **Efficiency:** Keep one reasoning core small and sharp.  
+- 🌍 **Scalability:** Add or update languages by swapping STAs.  
+- 🛠️ **Maintainability:** Upgrade individual adapters without retraining the whole system.  
+- 📱 **Small Models:** Perfect for low-resource environments, edge devices, and startups.  
+
+---
+
+## Example Conversation Flows
+```text
+User: Translate "my name is Adam" into German.
+CLM → <to:de> my name is Adam </to>
+STA → "Mein Name ist Adam"
+
+User (in Spanish): "¿Cuánto es 12 + 7?"
+Input STA (es→en) → "How much is 12 + 7?"
+CLM → "The answer is <to:es> 19 </to>"
+Output STA → "La respuesta es 19"