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

python

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/