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+ ---
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+ license: mit
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+ license_link: https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE
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+ language:
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+ - tr
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+ pipeline_tag: text-generation
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+ tags:
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+ - phi
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+ - nlp
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+ - instruction-tuning
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+ - turkish
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+ - chat
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+ - conversational
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+ inference:
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+ parameters:
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+ temperature: 0.7
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+ widget:
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+ - messages:
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+ - role: user
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+ content: "Internet'i nasıl açıklayabilirim?"
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+ library_name: transformers
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+ ---
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+
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+ # Phi-4 Turkish Instruction-Tuned Model
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+
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+ 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.
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+
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+ ## Model Summary
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+
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+ | | |
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+ |-------------------------|-----------------------------------------------|
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+ | **Developers** | Baran Bingöl (Hugging Face: [barandinho](https://huggingface.co/barandinho)) |
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+ | **Base Model** | [microsoft/phi-4](https://huggingface.co/microsoft/phi-4) |
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+ | **Architecture** | 14B parameters, dense decoder-only Transformer|
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+ | **Training Data** | 55K Turkish instruction samples |
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+ | **Context Length** | 16K tokens |
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+ | **License** | MIT ([License Link](https://huggingface.co/microsoft/phi-4/resolve/main/LICENSE)) |
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+
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+ ## Intended Use
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+
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+ ### Primary Use Cases
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+ - Turkish conversational AI systems
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+ - Chatbots and virtual assistants
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+ - Educational tools for Turkish users
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+ - General-purpose text generation in Turkish
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+
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+ ### Out-of-Scope Use Cases
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+ - High-risk domains (medical, legal, financial advice) without proper evaluation
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+ - Use in sensitive or safety-critical systems without safeguards
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+
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+ ## Usage
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+
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+ ### Input Formats
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+
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+ Given the nature of the training data, `phi-4` is best suited for prompts using the chat format as follows:
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+
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+ ```bash
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+ <|im_start|>system<|im_sep|>
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+ Sen yardımsever bir yapay zekasın.<|im_end|>
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+ <|im_start|>user<|im_sep|>
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+ Kuantum hesaplama neden önemlidir?<|im_end|>
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+ <|im_start|>assistant<|im_sep|>
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+ ```
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+
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+ ### With `transformers`
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+
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+ ```python
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+ import transformers
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+
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+ pipeline = transformers.pipeline(
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+ "text-generation",
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+ model="barandinho/phi4-turkish-instruct",
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+ model_kwargs={"torch_dtype": "auto"},
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+ device_map="auto",
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+ )
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+
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+ messages = [
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+ {"role": "system", "content": "Sen yardımsever bir yapay zekasın."},
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+ {"role": "user", "content": "Kuantum hesaplama neden önemlidir?"},
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+ ]
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+
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+ outputs = pipeline(messages, max_new_tokens=128)
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+ print(outputs[0]["generated_text"][-1])
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+ ```