Create Edge‑Ready AI in One Line No Data Required
Auto‑generate synthetic training data, fit an ultra‑compact model, and deploy anywhere—from microcontrollers to mobile apps—with a single command..
docker run --rm -v $(pwd):/app/models -e OPEN_ROUTER_API_KEY="YOUR_OPEN_ROUTER_KEY_HERE" \ docker run --rm -v $(pwd):/app/models -e
ghcr.io/whitelightning-ai/whitelightning:latest -p="Classify customer reviews as positive or negative sentiment" OPEN_ROUTER_API_KEY="YOUR_KEY_HERE"
ghcr.io/whitelightning-ai/whitelightning:
latest -p="Classify customer reviews
as positive or negative sentiment"
🧠 - INFO - Generate Edge Cases: True (Target Volume per class: 5)
🧠 - INFO - Successfully generated initial configuration.
🧠 - INFO - DataGenerator initialized. Config Model: 'x-ai/grok-3-beta', Model: 'openai/gpt-4o-mini'
🧠 - INFO - Prompt Refinement Cycles: 1 🧠 Created 1000 examples
🧠 - INFO - Generate Edge Cases: True (Target Volume per class: 50) 🧠 Generate Edge Cases...
📦 - INFO - === Starting Data Generation & Model Training Process === 📦 Starting training process...
📦 - INFO - Classification type: multiclass 📦 Type: multiclass
📦 - INFO - Class labels: ['negative', 'neutral', 'positive'] (Count: 3) 📦 Labels: negative, neutral, positive
📦 - INFO - --- Edge Case Generation Finished --- 📦 Edge cases generated
⚙️ - INFO - Starting model training using tensorflow strategy... ⚙️ Training started
📈 ━━━━━━━━━━━━━━━━━━━━ Epoch 1/20 - accuracy: 0.4164 - loss: 0.6194 📈 Epoch 1/20 - accuracy: 0.4164
📈 ━━━━━━━━━━━━━━━━━━━━ Epoch 20/20 - accuracy: 1.0000 - loss: 5.3911e-05 📈 Epoch 20/20 - accuracy: 1.0000
✅ - INFO - Test set evaluation - Loss: 0.0006, Accuracy: 1.0000 ✅ Test accuracy: 1.0000
📤 - INFO - Model exported to ONNX: 📤 Model exported
models_multiclass/customer_review_classifier/customer_review_classifier.onnx customer_review_classifier.onnx
⚡ - INFO - === Data Generation & Model Training Process Finished. Duration: 0:10:42 === ⚡ Process completed in 10:42
Features
STOP PAYING FOR CLOUD APIs
Don't rent intelligence by the query. Own your models and run them locally without recurring API costs.
RUN IT ANYWHERE
Deploy on your old laptop, a Pi Zero, a potato. No GPU required. Optimized for low-resource environments.
CREATE MODELS WITHOUT REAL DATA
Ask an LLM to generate synthetic training data. Build models without compromising privacy or when data is scarce.
CONTROL YOUR DATA
No creepy telemetry. No vendor lock-in. Your data stays on your devices where it belongs.