Beta

Explore
Marketplace
Neural Labs
Chat
Wallet
Docs

Beta

Explore Marketplace Neural Labs Wallet Docs

Build

Manage

My assets Manage wallet Organization

Community

Discord X (Twitter)Telegram

Docs Privacy Policy Terms and Conditions

Proud member of

Proud member of

Docs Cookie Policy

Privacy Policy Terms and Conditions

© 2026 AlphaNeural AI. All rights reserved.

qwen3-8B-SFT – AI Model by Mushari440 | AlphaNeural AI

You can deploy this model and start earning money today!

Mushari440/
qwen3-8B-SFT

like

0

text-generation

text-generation-inference

endpoints_compatible

Views

No views yet

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))