Model Export Helper
Simplifies exporting trained models from various frameworks to common formats like ONNX for easy deployment.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add model-export-helper npx -- -y @trustedskills/model-export-helper
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"model-export-helper": {
"command": "npx",
"args": [
"-y",
"@trustedskills/model-export-helper"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill assists in exporting machine learning models to various formats. It can handle different model types and export them as ONNX, CoreML, or TensorFlow Lite files. The tool simplifies the often complex process of converting models for deployment on diverse platforms and devices.
When to use it
- You need to deploy a PyTorch model to an iOS device using CoreML.
- You want to optimize a TensorFlow model for mobile devices with TensorFlow Lite.
- You're integrating a machine learning model into a cross-platform application requiring ONNX format.
- You require a standardized export of your model for sharing or further processing.
Key capabilities
- Exports models to ONNX format
- Exports models to CoreML format
- Exports models to TensorFlow Lite format
- Supports various model types (unspecified)
Example prompts
- "Export this PyTorch model to ONNX."
- "Convert the current TensorFlow model into a CoreML file for iOS deployment."
- "Generate a TensorFlow Lite version of my machine learning model."
Tips & gotchas
The skill's effectiveness depends on the underlying framework and model architecture. Ensure your environment has the necessary dependencies (e.g., PyTorch, TensorFlow) installed before using this skill.
Tags
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