Chan-Y/TurkishReasoner-Gemma3-1B

TurkishReasoner-Gemma3-1B

Model Description

TurkishReasoner-Gemma1B is a lightweight Turkish reasoning model fine-tuned from Google's Gemma3-1B. Despite its compact size, this model delivers impressive reasoning capabilities in Turkish, making it ideal for deployment in resource-constrained environments while maintaining high-quality step-by-step reasoning.

Key Features

• —Built on Google's efficient Gemma3-1B foundation
• —Fine-tuned specifically for Turkish reasoning tasks
• —Optimized for deployment on devices with limited resources
• —Delivers structured reasoning with clearly formatted solutions
• —Efficient text-only processing for reasoning tasks
• —32K token context window

Technical Specifications

• —Base Model: Google/Gemma3-1B
• —Parameters: 1 billion
• —Input: Text only
• —Hardware Requirements: ~4GB VRAM
• —Training Infrastructure: NVIDIA T4 GPU

Usage

This model is ideal for applications requiring reasoning capabilities in resource-constrained environments:

• —Mobile applications with Turkish reasoning capabilities
• —Educational tools for deployment on standard consumer hardware
• —Embedded systems requiring compact reasoning abilities
• —Local inference on personal computers with limited GPU resources

Example Usage

from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
from peft import PeftModel
import torch

base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-3-1b-it")
model = PeftModel.from_pretrained(base_model, "Chan-Y/TurkishReasoner-Gemma3-1B").to("cuda")
tokenizer = AutoTokenizer.from_pretrained("unsloth/gemma-3-1b-it")

pipe = pipeline(
    "text-generation",
    model=model,
    tokenizer=tokenizer,
    max_new_tokens=512,
    do_sample=True,
    temperature=0.7,
    top_p=0.95,
)

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, return_full_text=False)[0]["generated_text"]
print(response)

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

• —Cihan Yalçın: https://www.linkedin.com/in/chanyalcin/
• —Şevval Nur Savcı: https://www.linkedin.com/in/%C5%9Fevval-nur-savc%C4%B1/