Onnx Converter
- 53 installs
- 2.6k repo stars
- Updated August 5, 2026
- jeremylongshore/claude-code-plugins-plus-skills
Converts machine-learning models to the ONNX format for portable, cross-framework deployment.
About
Converts ML models into ONNX for interoperable deployment. A developer uses it when porting a trained model across runtimes.
- Auto-activates on onnx converter requests
- Part of the ML Deployment category
Onnx Converter by the numbers
- 53 all-time installs (skills.sh)
- Ranked #916 of 2,064 Data Science & ML skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/jeremylongshore/claude-code-plugins-plus-skills --skill onnx-converterAdd your badge
Show developers this skill is listed on Skillselion. Paste this into your README.
| Installs | 53 |
|---|---|
| repo stars | ★ 2.6k |
| Last updated | August 5, 2026 |
| Repository | jeremylongshore/claude-code-plugins-plus-skills ↗ |
What it does
Converts machine-learning models to the ONNX format for portable, cross-framework deployment.
Files
Onnx Converter
Overview
This skill provides automated assistance for onnx converter tasks within the ML Deployment domain.
When to Use
This skill activates automatically when you:
- Mention "onnx converter" in your request
- Ask about onnx converter patterns or best practices
- Need help with machine learning deployment skills covering model serving, mlops pipelines, monitoring, and production optimization.
Instructions
1. Provides step-by-step guidance for onnx converter 2. Follows industry best practices and patterns 3. Generates production-ready code and configurations 4. Validates outputs against common standards
Examples
Example: Basic Usage Request: "Help me with onnx converter" Result: Provides step-by-step guidance and generates appropriate configurations
Prerequisites
- Relevant development environment configured
- Access to necessary tools and services
- Basic understanding of ml deployment concepts
Output
- Generated configurations and code
- Best practice recommendations
- Validation results
Error Handling
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Resources
- Official documentation for related tools
- Best practices guides
- Community examples and tutorials
Related Skills
Part of the ML Deployment skill category. Tags: mlops, serving, inference, monitoring, production
Related skills
Microsoft FoundryDeploy, evaluate, and continuously improve Microsoft Foundry agents from a single agent interface.490k1.3k
Ai Research ReproductionOrchestrate trustworthy, auditable reproduction of deep learning repositories directly from their READMEs.176k511Run TrainSafely execute selected deep learning training commands with standardized evidence capture.176k511Explore RunSafely run isolated exploratory experiments with clear recording and conservative selection before committing changes.176k511Paper Context ResolverFetch precise reproduction-critical details like dataset splits, preprocessing steps, or evaluation protocols from the original academic paper when the repo README leav141k511Repo Intake And PlanScan unfamiliar AI research repositories and receive a minimal, trustworthy reproduction target before investing significant time.140k511