Overview

TypeScript-SLM-7B-Reasoning-Full is a 7.6 billion parameter model developed by Sylvester Francis, built upon the deepseek-ai/DeepSeek-R1-Distill-Qwen-7B base. It has been fine-tuned using LoRA adapters specifically for advanced TypeScript reasoning tasks. The model is designed to provide detailed, step-by-step explanations and solutions for complex coding challenges, and includes GGUF quantization for efficient local inference with tools like Ollama.

Key Capabilities

• TypeScript Reasoning & Debugging: Explains bugs, suggests fixes, and provides clear reasoning traces.
• Code Generation: Generates strongly-typed code for popular frameworks including React, Next.js, Angular, and Node.js.
• Refactoring & API Design: Assists with code refactoring and discussions on API design choices.
• Framework-Aware: Produces solutions that adhere to framework best practices.

Intended Uses

This model is primarily intended for TypeScript-related tasks such as debugging, refactoring, and guided code generation. It is not designed for general natural language chat, safety-sensitive applications, or factual tasks outside of its specialized domain. Users should review generated code for correctness and security before deployment.