Qwen3-8B-SFT-V2

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

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Mushari440/Qwen3-8B-SFT-V2")
model = AutoModelForCausalLM.from_pretrained("Mushari440/Qwen3-8B-SFT-V2")

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))