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Check out the documentation for more information.

iOS ML Artifacts

Pre-built iOS ML artifacts for on-device inference. Includes ONNX Runtime xcframework, sqlite-vec static libraries, and embedding models optimized for iOS.

Contents

1. ONNX Runtime iOS XCFramework

  • Version: 1.22.0
  • Size: ~49MB
  • Architectures:
    • ios-arm64 - Physical iOS devices
    • ios-arm64-simulator - iOS Simulator (Apple Silicon)
  • Features: CoreML execution provider for Apple Neural Engine acceleration

2. sqlite-vec Static Libraries

  • Version: 0.1.6
  • Size: ~340KB per architecture
  • Architectures:
    • ios-arm64 - Physical iOS devices
    • ios-arm64-simulator - iOS Simulator (Apple Silicon)
  • Purpose: Vector similarity search extension for SQLite

3. BGE-Small Text Embedding Model

  • Model: bge-small-en-v1.5-int8.onnx
  • Size: 32MB (INT8 quantized)
  • Dimensions: 384
  • Use Case: Text embeddings for semantic search
  • Includes: tokenizer.json for text preprocessing

Quick Start

Download from GitHub Releases

# Download all artifacts
gh release download v1.0.0 --repo vannmex/vannmex-ios-ml-artifacts

# Or download specific files
gh release download v1.0.0 --pattern "onnxruntime-*.zip" --repo vannmex/vannmex-ios-ml-artifacts
gh release download v1.0.0 --pattern "sqlite-vec-*.zip" --repo vannmex/vannmex-ios-ml-artifacts
gh release download v1.0.0 --pattern "bge-small-*.zip" --repo vannmex/vannmex-ios-ml-artifacts

Download from Hugging Face

# Install HF CLI
brew install huggingface-cli

# Download all artifacts
hf download vannmex/ios-ml-artifacts --local-dir ./artifacts

# Or download specific files
hf download vannmex/ios-ml-artifacts onnxruntime/onnxruntime.xcframework --local-dir ./onnxruntime

Integration

ONNX Runtime in Xcode

  1. Unzip onnxruntime-ios-1.22.0.xcframework.zip
  2. Drag onnxruntime.xcframework into your Xcode project
  3. In Build Phases > Link Binary With Libraries, ensure it's listed
  4. Add to Framework Search Paths if needed

sqlite-vec in Rust/Tauri

// Load the extension
unsafe {
    conn.load_extension_enable()?;
    conn.load_extension("libsqlite_vec0", None)?;
    conn.load_extension_disable()?;
}

BGE-Small Embedding Model

use ort::{Session, SessionBuilder};

let session = SessionBuilder::new()?
    .with_execution_providers([CoreMLExecutionProvider::default().build()])?
    .with_model_from_file("bge-small-en-v1.5-int8.onnx")?;

Checksums

Verify file integrity with SHA-256:

shasum -a 256 *.zip

License

  • ONNX Runtime: MIT License
  • sqlite-vec: MIT License
  • BGE-Small: MIT License (BAAI)

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