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metadata
license: mit
license_link: https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE
language:
  - tr
pipeline_tag: text-generation
tags:
  - phi
  - nlp
  - instruction-tuning
  - turkish
  - chat
  - conversational
inference:
  parameters:
    temperature: 0.7
widget:
  - messages:
      - role: user
        content: Internet'i nasıl açıklayabilirim?
library_name: transformers

Phi-4 Turkish Instruction-Tuned Model

This model is a fine-tuned version of Microsoft's Phi-4 model for Turkish instruction-following tasks. It was trained on a 55,000-sample Turkish instruction dataset, making it well-suited for generating helpful and coherent responses in Turkish.

Model Summary

Developers Baran Bingöl (Hugging Face: barandinho)
Base Model microsoft/phi-4
Architecture 14B parameters, dense decoder-only Transformer
Training Data 55K Turkish instruction samples
Context Length 16K tokens
License MIT (License Link)

Intended Use

Primary Use Cases

  • Turkish conversational AI systems
  • Chatbots and virtual assistants
  • Educational tools for Turkish users
  • General-purpose text generation in Turkish

Out-of-Scope Use Cases

  • High-risk domains (medical, legal, financial advice) without proper evaluation
  • Use in sensitive or safety-critical systems without safeguards

Usage

Input Formats

Given the nature of the training data, phi-4 is best suited for prompts using the chat format as follows:

<|im_start|>system<|im_sep|>
Sen yardımsever bir yapay zekasın.<|im_end|>
<|im_start|>user<|im_sep|>
Kuantum hesaplama neden önemlidir?<|im_end|>
<|im_start|>assistant<|im_sep|>

With transformers

import transformers

pipeline = transformers.pipeline(
    "text-generation",
    model="barandinho/phi4-turkish-instruct",
    model_kwargs={"torch_dtype": "auto"},
    device_map="auto",
)

messages = [
    {"role": "system", "content": "Sen yardımsever bir yapay zekasın."},
    {"role": "user", "content": "Kuantum hesaplama neden önemlidir?"},
]

outputs = pipeline(messages, max_new_tokens=128)
print(outputs[0]["generated_text"][-1])