This repository contains a machine learning-based credit scoring system tailored for Zimbabwe’s unique economic and financial landscape. The model leverages pre-trained base models, fine-tuned with local financial data, to provide accurate credit risk assessments. Designed for both B2B and C2B use cases
active 2025-01-05 → 2025-02-12 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 39 days from 2025-01-05 to 2025-02-12. Pushes: 13 total, peak 4 in a day. Pull requests: 6 total, peak 2 in a day. Issues: 0 total, peak 0 in a day. Comments: 5 total, peak 3 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| nyashaChiza | 19 | 13 | 6 | 0 |
| coderabbitai[bot] | 4 | 0 | 0 | 3 |
| vercel[bot] | 2 | 0 | 0 | 2 |
Recent activity
Latest issues, pull requests and releases
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.