onnx-rust-integration
OfficialIntegrate ONNX models into Rust applications with ort crate
AuthorHopeArtOrg
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps developers load and run ONNX models within Rust applications using the ort crate, enabling the use of pre-trained machine learning models in Rust projects.
Core Features & Use Cases
- ONNX Model Loading: Load ONNX models into a Rust session for execution.
- Platform-Specific Execution: Supports CUDA, DirectML, CoreML, XNNPACK, and CPU execution providers.
- Model Path Resolution: Prioritizes downloaded models, bundled resources, and dev-mode paths.
- Model Execution: Run inferences on input data with support for extra index inputs.
- Use Case: A developer can integrate this Skill into a Rust application to utilize pre-trained ONNX models for tasks like image classification or natural language processing.
Quick Start
Load the ONNX model 'noise_algorithm.onnx' and run an inference on the input data 'image.png'.
Dependency Matrix
Required Modules
ort
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: onnx-rust-integration Download link: https://github.com/HopeArtOrg/hope-re/archive/main.zip#onnx-rust-integration Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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