VGreatVig07/phi3-mini-Docuanalyzer

🧠 Phi-3 Mini Fine-Tuned (GGUF) — Legal Assistant

This is a LoRA fine-tuned version of microsoft/phi-3-mini-4k-instruct converted to GGUF format for use with llama.cpp, Ollama, or compatible runtimes.

It was trained on legal documents to act as a context-aware legal assistant that can answer questions from uploaded contracts and policies.

🔧 Model Details

• Base model: microsoft/phi-3-mini-4k-instruct
• Fine-tuned with: LoRA (PEFT) + TRLL SFTTrainer
• Converted to GGUF using: convert_hf_to_gguf.py from llama.cpp

🛠 How to Use

🔁 With llama.cpp

./main -m phi3-finetuned.gguf -p "What rights does this contract give me?"

🔁 With 🐍 With Python + llama-cpp-python

from llama_cpp import Llama

llm = Llama(model_path="phi3-finetuned.gguf")
output = llm("Summarize the terms of this agreement.")
print(output)

🔁 With 🤖 With Ollama (if merged)

ollama create phi3-legal -f Modelfile
ollama run phi3-legal

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🧾 Use Cases

This fine-tuned model is intended for legal document analysis and Q&A applications.

Example questions it can answer:

• "Can this agreement be terminated without prior notice?"
• "Do I have refund rights under this policy?"
• "What are the obligations mentioned in clause 3?"
• "Is there an arbitration clause in this contract?"

It is designed to provide helpful, non-legal-advice explanations by summarizing and interpreting clauses based on the uploaded text context.

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📁 Files

File	Description
phi3-finetuned.gguf	The GGUF format model file for inference
README.md	Description and usage guide (this file)
Modelfile (optional)	Ollama model recipe (if you use Ollama)

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🧠 Credits

• Project: DocuAnalyzer AI
• Author: Vighnesh M S (@VGreatVig07)
• Fine-tuning: Performed using Hugging Face transformers, trl, and PEFT (LoRA)
• Conversion: Model converted to .gguf format using llama.cpp's convert_hf_to_gguf.py

Thanks to open-source contributions from:

• Microsoft (Phi-3 base model)
• Hugging Face ecosystem
• llama.cpp team