Model Details
- Developed by: Destin Biringanine
- Entreprise: Code, Growth Alive
- Base model:
unsloth/gemma-4-E2B-it-unsloth-bnb-4bit
- Fine-tuning: LoRA (PEFT)
- Framework: Unsloth
- License: Apache-2.0
Intended Use
This model is designed for enterprise decision-support tasks, including:
- Contract analysis
- Invoice understanding
- Procurement intelligence
- Supplier risk assessment
- Financial document analysis
- Business reporting
- Explainable recommendations
The model follows a structured reasoning process consisting of:
- Evidence
- Reasoning
- Confidence
- Business Impact
- Recommended Actions
Training
The adapter was fine-tuned using Unsloth on a structured business reasoning dataset.
The objective was not to teach new business knowledge, but to improve the model's ability to produce consistent, transparent, and explainable business reasoning.
Example
Supplier A has delayed deliveries for three consecutive months.The defect rate increased by 18%.The contract expires next month.Should the contract be renewed?
Output
{ "decision": "Do not renew without corrective actions.", "evidence": [ "Three consecutive delivery delays", "18% increase in defect rate" ], "reasoning": "Operational performance has consistently deteriorated, increasing supply-chain risk.", "confidence": 0.95, "business_impact": "High operational risk", "recommended_actions": [ "Request a corrective action plan", "Evaluate alternative suppliers", "Conduct a supplier performance review" ]}
Limitations
This model is intended for research and demonstration purposes.
It should be used as a decision-support assistant rather than an autonomous decision-maker and performs best when combined with an external knowledge base or retrieval system.
Acknowledgements
This project was developed for the Build with Google Gemma Hackathon using:
- Google Gemma
- Unsloth
- Hugging Face Transformers
- PEFT
- PyTorch