GraphCanon updated Oct 5, 2026 · GitHub synced Oct 5, 2026
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Decision brief
Model-Fingerprint is a toolset for creating instructional fingerprints of large language models using CUDA 11.3 and PyTorch 2.0.
Good fit when
- Use Model-Fingerprint when you need to fingerprint large language models for evaluation or observability purposes, especially in research contexts involving CUDA 11.3 and PyTorch 2.0 environments.
- Consider this toolset if your project involves creating fingerprints based on specific templates like Simple Template or Dialogue Template to analyze model behavior.
Avoid when
- Do not use Model-Fingerprint if your development environment does not support CUDA 11.3 and PyTorch 2.0, as it may lead to incompatibility issues.
- Avoid this toolset if you need a solution that supports multiple versions of CUDA or Pytorch for flexibility across different hardware configurations without modification.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (816d since push)
- As of Oct 5, 2026
- Provenance
- Not a fork · Personal account
- As of Oct 5, 2026
- Security (OSV)
- No criticals
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Model-FingerprintSimilar 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 toolset for creating instructional fingerprints of large language models using CUDA 11.3 and PyTorch 2.0.
Capability facts
- Languages
- python
Source: github.language · Oct 5, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Oct 5, 2026)
This project is developed using CUDA 11.3, PyTorch 2.0, python 3.9.Source link
Tags
README
Instructional Fingerprinting <div align="center" <strong <h3 <a href="https://arxiv.org/abs/2401.12255" Instructional Fingerprinting of Large Language Models</a </h3 </strong </div <div align="center" <span <a href="https://cnut1648.github.io/" <strong Jiashu Xu</strong </a ,&nbs...
For agents
This page has a .md twin and JSON over the API.