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| [phi-4_hb8_6bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_6bpw) | 6.00 bits per weight | 11.8 GB |
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| [phi-4_hb8_7bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_7bpw) | 7.00 bits per weight | 13.5 GB |
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| [phi-4_hb8_8bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_8bpw) | 8.00 bits per weight | 15.2 GB |
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| [phi-4_hb8_6bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_6bpw) | 6.00 bits per weight | 11.8 GB |
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| [phi-4_hb8_7bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_7bpw) | 7.00 bits per weight | 13.5 GB |
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| [phi-4_hb8_8bpw](https://huggingface.co/cmh/phi-4_exl2/tree/hb8_8bpw) | 8.00 bits per weight | 15.2 GB |
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# Phi-4 Model Card
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[Phi-4 Technical Report](https://arxiv.org/pdf/2412.08905)
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## Model Summary
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|-------------------------|-------------------------------------------------------------------------------|
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| **Developers** | Microsoft Research |
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| **Description** | `phi-4` is a state-of-the-art open model built upon a blend of synthetic datasets, data from filtered public domain websites, and acquired academic books and Q&A datasets. The goal of this approach was to ensure that small capable models were trained with data focused on high quality and advanced reasoning.<br><br>`phi-4` underwent a rigorous enhancement and alignment process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures |
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| **Architecture** | 14B parameters, dense decoder-only Transformer model |
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| **Inputs** | Text, best suited for prompts in the chat format |
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| **Context length** | 16K tokens |
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## Usage
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### Input Formats
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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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```bash
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<|im_start|>system<|im_sep|>
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You are a medieval knight and must provide explanations to modern people.<|im_end|>
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<|im_start|>user<|im_sep|>
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How should I explain the Internet?<|im_end|>
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<|im_start|>assistant<|im_sep|>
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```
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