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KRAFTYUX/
phi3-prompt-engineer-gguf

Name: phi3-prompt-engineer-gguf
Availability: InStock

microsoft/Phi-3-mini-4k-instruct

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Phi-3 Prompt Engineer (GGUF)

This repository contains GGUF quantized versions of the Phi-3 Prompt Engineer model, fine-tuned to excel at refining user requests into detailed, structured prompts for LLMs.

Model Description

Base Model: microsoft/Phi-3-mini-4k-instruct
Fine-tuning: LoRA adapters trained on a custom dataset of prompt refinement examples.
Purpose: To act as a specialized "Prompt Engineer" agent, converting vague user ideas into high-quality, actionable system instructions and prompts.

Available Quantizations

The following GGUF files are available for download. Q4_K_M is recommended for most users as it balances performance and quality perfectly.

Filename	Quantization	Size	SHA256 Checksum
phi3-prompt-engineer-f16.gguf	F16	7.12 GB	`1bc8a41027c400eda38d5dc9cf97fcf0a4617072d2c3c132b922dd2589783c16`
phi3-prompt-engineer-q4_k_m.gguf	Q4_K_M	2.23 GB	`cc840e37e0f21c97bf158211a2f0dda1096294ee47ab3f199da854cc841c39f7`
phi3-prompt-engineer-q5_k_m.gguf	Q5_K_M	2.62 GB	`218b8021b5f1b1efb2e0914d939f5464d8cb790ef9d9e35eaa05e1b8b3cc560f`
phi3-prompt-engineer-q6_k.gguf	Q6_K	2.92 GB	`4cf033bfe14c43ebf84e47f7184f2f0f5286a30a2c87927d59aa95d9b4a455d5`
phi3-prompt-engineer-q8_0.gguf	Q8_0	3.78 GB	`2aa4f14b038c01a50ad8e3306832a25b8c6f704aa1d9efa29a88856dee924fce`

Usage

Ollama

You can use these files directly with Ollama.

Create a Modelfile:

dockerfile
1FROM ./phi3-prompt-engineer-q4_k_m.gguf 2SYSTEM "You are an Expert Prompt Engineer. Your goal is to refine the following user request into a clear, structured, and detailed prompt."
Create and run the model:

bash
1ollama create phi3-pe -f Modelfile 2ollama run phi3-pe

llama.cpp

./main -m phi3-prompt-engineer-q4_k_m.gguf -p "You are an Expert Prompt Engineer. Refine this: make a snake game in python"

Training Data

The model was trained on a proprietary dataset (raw_dataset.jsonl) consisting of:

Input: Raw, often vague user requests (e.g., "make a login page").
Output: Detailed, structured Prompt Engineering responses including personas, constraints, and specific requirements.
Focus: Web development, Python scripting, creative writing, and system design tasks.

License

MIT

KRAFTYUX/phi3-prompt-engineer-gguf