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LoRA-Fine-Tuned Commercial Lease Clause Risk Classifier

Llama 3.1 8B fine-tuned with LoRA/QLoRA on a curated corpus of EU-jurisdiction commercial lease agreements. Classifies 23 clause types, flags 11 risk patterns against standard templates, and outputs a structured JSON risk report with per-clause remediation notes. A 60-page lease is processed in under 10 seconds.

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What We Built

Training Dataset Curation

4,000 EU-jurisdiction commercial lease agreements de-identified and annotated with clause type labels and risk pattern tags — forming the fine-tuning corpus for the model.

LoRA/QLoRA Fine-Tuning

Llama 3.1 8B adapted via LoRA/QLoRA on a single A10G GPU — learning 23 clause type labels and 11 risk pattern classes specific to EU commercial lease language and structure.

Structured JSON Risk Output

Every clause extracted with: type classification, risk level (LOW / MEDIUM / HIGH), a plain-language deviation summary, and a specific remediation note suggesting the corrected clause wording.

Baseline Comparison Engine

Delta analysis between each extracted clause and the client's own standard template — highlighting deviations, missing protections, and non-standard additions in a structured diff view.

FastAPI Serving with PDF Preprocessing

REST API endpoint accepts uploaded PDFs and Word documents. pdfplumber with OCR fallback handles scanned and image-based leases — the model ingests clean text regardless of source format.

Colour-Coded Report Export

Word and PDF reports generated automatically — each clause highlighted green, amber, or red by risk level, with remediation notes inserted as tracked changes for direct solicitor review.

Technologies Used

Llama 3.1 8B
LoRA / QLoRA
Unsloth
HuggingFace
PyTorch
FastAPI
pdfplumber
Tesseract OCR
python-docx
PostgreSQL
Docker
NVIDIA A10G

Key Outcomes

91%

Clause classification accuracy across all 23 clause types

<10s

Processing time per 60-page commercial lease document

~4 hrs

Junior associate review time saved per contract

Need Something Similar?

Tell us about your document type, jurisdiction, and labelling requirements. We will recommend the best fine-tuning approach and give you an honest assessment.