The Phi-3 Mini 4K Instruct model is a lightweight and robust tool designed for various text generation tasks. Created by Microsoft, this model boasts 3.8 billion parameters and delivers impressive performance across language understanding and reasoning tasks. In this article, we’ll guide you through how to set up and use this powerful model effectively.

Model Overview

The Phi-3 Mini 4K Instruct model is trained with both synthetic data and filtered publicly available data to ensure high-quality outputs. It offers two variants based on context length: 4K and the extended 128K. Post-training processes have further tuned the model for instruction-following tasks and safety measures.

Getting Started with the Model

To begin using the Phi-3 Mini 4K Instruct model, follow these simple steps:

• Step 1: Ensure you have the Sanctum App installed.
• Step 2: Open the Sanctum App and select the Phi 3 model preset.
• Step 3: Frame your prompts according to the template provided below:

system
    system_prompt.
    enduserprompt
    

Understanding the Parameters

The Phi-3 Mini 4K Instruct has various quantization methods impacting the model’s size and required memory. Think of the model’s memory requirements like fitting different sizes of boxes into your storage space. Depending on how you quantize the model, some will require more room than others:

• Q2_K: Size: 1.45 GB | Memory: 5.05 GB
• Q3_K_S: Size: 1.68 GB | Memory: 5.27 GB
• Q4_0: Size: 2.18 GB | Memory: 5.73 GB
• Q6_K: Size: 3.14 GB | Memory: 6.62 GB
• fp16: Size: 7.64 GB | Memory: 10.82 GB

Troubleshooting Tips

Even the best models can encounter hiccups. Here are some troubleshooting ideas:

• Memory Issues: If the app crashes or you experience slow performance, make sure you have sufficient RAM. Check the required memory for your selected quantization method.
• Prompt Errors: Double-check your prompt format. Ensure it matches the expected structure to avoid generating incorrect outputs.
• Model Availability: If the model is not responding, it may be temporarily offline. Try again later or switch to another configuration.

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Final Thoughts

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.