Razi SLM — Case Study | Ibrahem Qusay
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Razi SLM

An Arabic small language model project focused on accessible and responsible medical-language understanding.

At a Glance

Status:Active Development
Category:AI Research
Built by:Ibrahem Qusay
Technologies:PyTorch, Ollama, Python

Overview

Medical language — lab results, doctor instructions, specialty terminology — is often opaque to Arabic-speaking patients. Razi SLM is a local, small language model trained to simplify that language for general health education, run under resource constraints without depending on a cloud API.

Capabilities

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Boundaries

Razi SLM does not diagnose, prescribe, or replace a physician. It is a plain-language explainer, not a clinical tool, and carries no medical-device certification.

Frequently Asked Questions

What is Razi SLM?

A local, small Arabic language model trained to translate medical language — lab results, doctor instructions, specialty terms — into plain-language explanations for general health education.

Does Razi SLM diagnose or prescribe?

No. It does not diagnose, prescribe, or replace a physician — it's a plain-language explainer with no medical-device certification, not a clinical tool.

Why run it locally instead of via a cloud API?

Razi SLM is built to run under resource constraints without depending on a cloud API, keeping medical-language explanation usable in low-connectivity or privacy-sensitive settings.