Turkish-LLM-14B-Instruct

Turkish-LLM-14B-Instruct

A Turkish-enhanced 14B model fine-tuned from Qwen2.5-14B-Instruct with QLoRA on 242K Turkish instruction examples.

Part of the Turkish LLM Family.

Highlights

• 14B parameters - strong performance with moderate hardware requirements
• Outperforms base on MMLU-TR (+0.30 vs Qwen2.5-14B-Instruct)
• Live demo - Try it on Spaces
• GGUF available - Q4/Q5/Q8/F16 quantizations

Benchmark Results

Quick Start

With Ollama

ollama run hf.co/ogulcanaydogan/Turkish-LLM-14B-Instruct-GGUF:Q4_K_M

With Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("ogulcanaydogan/Turkish-LLM-14B-Instruct", torch_dtype="auto", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("ogulcanaydogan/Turkish-LLM-14B-Instruct")

messages = [
    {"role": "system", "content": "Sen yardimci bir Turkce asistansin."},
    {"role": "user", "content": "Yapay zekanin egitim sektorundeki etkilerini acikla."}
]
text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer([text], return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Training Details

Turkish LLM Family

Citation

@misc{aydogan2026turkishllm,
  title={Turkish LLM Family: Open-Source Turkish Language Models},
  author={Ogulcan Aydogan},
  year={2026},
  url={https://huggingface.co/collections/ogulcanaydogan/turkish-llm-family-69b303b4ef1c36caffca4e94}
}