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metadata
base_model: unsloth/qwen2.5-3b-instruct-unsloth-bnb-4bit
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
  - grpo
  - qwen2.5
license: other
license_name: qwen-research
license_link: https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE
language:
  - tr

TurkishReasoner-Qwen2.5-3B

Model Description

TurkishReasoner-Qwen2.5-3B is a mid-sized Turkish reasoning model built on Qwen's efficient Qwen2.5-3B foundation. This model provides an excellent balance between performance and computational efficiency, delivering structured reasoning capabilities in Turkish while requiring moderate resources for deployment.

Key Features

  • Built on Qwen's efficient 3B parameter architecture
  • Specialized for Turkish reasoning with structured output format
  • Excellent balance between performance and resource requirements
  • Strong support for structured data and structured outputs
  • Enhanced instruction following for reasoning tasks
  • Support for multilingual context with Turkish optimization

Technical Specifications

  • Base Model: Qwen/Qwen2.5-3B
  • Parameters: 3.09 billion
  • Input: Text
  • Hardware Requirements: ~8GB VRAM
  • Training Infrastructure: NVIDIA T4 GPU

Usage

This model is ideal for applications requiring solid reasoning in Turkish with moderate computational resources:

  • Educational applications requiring detailed problem-solving
  • Mid-tier deployment environments with limited GPU resources
  • Applications balancing reasoning quality with efficiency requirements
  • Development and prototyping of reasoning-intensive applications

Example Usage

from transformers import pipeline

pipe = pipeline("text-generation", model="Chan-Y/TurkishReasoner-Qwen2.5-3B", device=0)

messages = [
    {"role": "system", "content": """Sen kullanıcıların isteklerine Türkçe cevap veren bir asistansın ve sana bir problem verildi.
Problem hakkında düşün ve çalışmanı göster.
Çalışmanı <start_working_out> ve <end_working_out> arasına yerleştir.
Sonra, çözümünü <SOLUTION> ve </SOLUTION> arasına yerleştir.
Lütfen SADECE Türkçe kullan."""},
    {"role": "user", "content": "121'in karekökü kaçtır?"},
]

response = pipe(messages)
print(response)

For more information or assistance with this model, please contact the developers: