WhiteLightning
WhiteLightning is an open-source CLI tool that enables developers to create fast, lightweight text classifiers that can run entirely offline by distilling large language models into compact ONNX models under 1MB.
https://whitelightning.ai/?ref=producthunt
Product Information
Updated:Aug 8, 2025
What is WhiteLightning
WhiteLightning, developed by Inoxoft, is an innovative command-line interface tool designed to democratize natural language processing (NLP) capabilities for edge devices and embedded systems. Released in 2025, this open-source solution addresses the growing need for intelligent, privacy-safe NLP in offline environments. Unlike traditional NLP solutions that rely on cloud APIs or large language models at runtime, WhiteLightning enables developers to create and run compact text classifiers locally without ongoing cloud dependencies.
Key Features of WhiteLightning
WhiteLightning is an open-source CLI tool that enables developers to create compact, efficient text classifiers by distilling large language models (LLMs) into lightweight ONNX models under 1MB. It allows for local-first AI capabilities without cloud dependencies, offering privacy-safe NLP solutions that can run entirely offline on edge devices and embedded systems.
Local-First Architecture: Operates completely offline without requiring cloud APIs or LLMs at runtime, enabling privacy-focused and infrastructure-independent deployment
Compact Model Output: Generates ultra-compact ONNX models under 1MB in size that can run on resource-constrained devices
Multi-Platform Compatibility: Exports models that can run natively in multiple programming languages including Python, JavaScript, C++, Rust, and Java
Docker-Based Deployment: Comes as a production-ready Docker image that works seamlessly across macOS, Linux, and Windows environments
Use Cases of WhiteLightning
Edge Device Processing: Enable NLP capabilities on IoT devices and embedded systems where cloud connectivity isn't available or reliable
Privacy-Sensitive Applications: Process sensitive text data locally in healthcare, financial, or government applications where data privacy is crucial
Mobile Applications: Integrate lightweight text classification capabilities into mobile apps without requiring constant server communication
Pros
No recurring API costs or cloud dependencies
Complete control over model deployment and data privacy
Highly portable and resource-efficient
Cons
Requires technical expertise to implement
Limited to classification tasks rather than full LLM capabilities
How to Use WhiteLightning
Install Docker: Ensure Docker is installed on your system as WhiteLightning runs as a Docker container
Get API Key: Obtain an OpenRouter API key which will be used to access large language models like GPT-4, Claude 4, or Grok
Create Working Directory: Create a directory where the generated models will be saved
Run Docker Command: Execute the Docker command with proper parameters: docker run --rm -v "$(pwd)":/app/models -e OPEN_ROUTER_API_KEY="YOUR_KEY_HERE" ghcr.io/inoxoft/whitelightning:latest
Define Classification Task: Use the -p flag to describe your classification task (e.g., -p "Categorize customer reviews as positive, neutral, or negative")
Wait for Processing: The tool will automatically generate synthetic training data, train a compact model, and evaluate its performance
Collect Output Model: Find the exported ONNX model in your working directory, which will be under 1MB in size
Deploy Model: Use the generated ONNX model in your application - compatible with multiple programming languages including Python, JavaScript, C++, Rust, Java
WhiteLightning FAQs
WhiteLightning is an open-source CLI tool developed by Inoxoft that converts large language models (like Claude 4, Grok 4, GPT-4) into tiny ONNX text classifiers that can run offline and locally.
WhiteLightning Video
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