OML-1.0-Fingerprinting
OML 1.0 via Fingerprinting: Open, Monetizable, and Loyal AI
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
OML-1.0-Fingerprinting focuses on leveraging fingerprinting techniques for the creation of open-source, monetizable AI models that ensure user fidelity and loyalty.
Good fit when
- When aiming to establish a direct connection with end-users through unique identification (fingerprinting) for enhancing personalized interactions.
- In scenarios where building an engaging user base committed to using specific AI products or services is necessary.
Avoid when
- If strict privacy policies and regulations prohibit the implementation of fingerprinting techniques, as this tool specifically utilizes such methods.
- When focusing on non-loyalty-based customer relationships, considering OML-Fingerprinting is tailored for establishing loyal user bases through unique identification technologies.
- Requirements:
- Min 4 GB RAM; Should be used with Python environment due to its primary language being Python.
Observed Jul 12, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (604d since push)
- As of Sep 19, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 19, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install OML-1.0-FingerprintingSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A repository focusing on the concept of creating open, monetizable, and loyal AI systems through fingerprinting techniques for fine-tuning.
Capability facts
- Languages
- python
Source: github.language · Sep 19, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 19, 2026)
- Make sure to have python >= 3.10.14 installed.Source link
Tags
README
🚀 Quick Start Detailed instructions on setting up environment for model fingerprinting are posted in [[ docs/setup.md ]](docs/setup.md). Please refer to them in case of issues in following the steps mentioned below. To get started, follow these steps: 1. Install Dependencies 📦...
For agents
This page has a .md twin and JSON over the API.