WhiteLightning

What is WhiteLightning?

WhiteLightning is a powerful tool that lets you create AI models quickly and easily. It helps you generate synthetic training data, build compact models, and deploy them anywhere, even on devices with low resources. With WhiteLightning, you can own your AI models and run them locally without needing expensive cloud APIs.

Benefits

Save Money on Cloud APIs

With WhiteLightning, you don't have to pay for cloud APIs. You can own your models and run them locally, saving you from recurring API costs.

Run AI Models Anywhere

Whether you have an old laptop, a Raspberry Pi, or even a low-resource device, WhiteLightning can deploy AI models there. You don't need a powerful GPU to run these models.

Build Models Without Real Data

WhiteLightning can generate synthetic training data using large language models (LLMs). This means you can build AI models even when real data is scarce or privacy is a concern.

Keep Your Data Private

WhiteLightning ensures that your data stays on your devices. There's no telemetry or vendor lock-in, so you have full control over your data.

Use Cases

Customer Review Classification

You can use WhiteLightning to classify customer reviews as positive, neutral, or negative. This can help businesses understand customer sentiment and improve their services.

Deploy on Low-Resource Devices

WhiteLightning is optimized for low-resource environments. You can deploy AI models on devices like Raspberry Pi or even older laptops, making it versatile for various applications.

Privacy-Focused AI Development

Since WhiteLightning generates synthetic data, it's ideal for situations where privacy is a concern. You can build AI models without compromising sensitive data.

How It Works

1. Generate Edge Cases: WhiteLightning starts by generating initial configuration and synthetic training data.
2. Data Generation & Model Training: The system then generates edge cases and trains the model using TensorFlow strategy.
3. Model Training: The model is trained over 20 epochs, achieving high accuracy.
4. Model Export: The trained model is exported to ONNX format, making it ready for deployment.
5. Process Completion: The entire process is completed in about 10 minutes and 42 seconds.

Technical Details

• Classification Type: Multiclass
• Class Labels: Negative, Neutral, Positive
• Model Accuracy: 1.0000
• Model Loss: 0.0006
• Model Export Path: modelsmulticlass/customerreviewclassifier/customerreview_classifier.onnx

WhiteLightning streamlines the process of creating edge-ready AI models, making it efficient and user-friendly.