---
library_name: transformers
tags:
- arabic
- sft
- qwen
---

# Qwen3-8B-SFT

## Model Details

- **Developed by:** Mushari Alothman  
- **Model type:** Causal Language Model  
- **Language(s):** Arabic, English  
- **License:** Apache 2.0  
- **Finetuned from:** Qwen3-8B-Base  

This is a supervised fine-tuned (SFT) Qwen3-8B model optimized for accurate, clean supervision across Arabic and English tasks.

## Intended Uses

### Direct Use
- Arabic & English MCQ answering  
- Context-based QA / RAG  
- General instruction following  

### Out-of-Scope Use
- Safety-critical or real-time decision making  
- Generating factual guarantees without verification  

## Training Summary

- **Training type:** Supervised Fine-Tuning (SFT)  
- **Precision:** bf16 mixed precision  
- **Data:** Curated Arabic & English datasets including:
  - MCQ 
  - QA / RAG / context understanding
  - General instruction data  

## How to Use

```python
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Mushari440/qwen3-8B-SFT")
model = AutoModelForCausalLM.from_pretrained("Mushari440/qwen3-8B-SFT")

inputs = tokenizer("سؤال: ما عاصمة السعودية؟", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=50)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
