---
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](https://huggingface.co/barandinho)) |
| **Base Model**          | [microsoft/phi-4](https://huggingface.co/microsoft/phi-4)                              |
| **Architecture**        | 14B parameters, dense decoder-only Transformer|
| **Training Data**       | 55K Turkish instruction samples              |
| **Context Length**      | 16K tokens                                   |
| **License**             | MIT ([License Link](https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE)) |

## 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: 

```bash
<|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`

```python
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])
```