ML Training Pipeline

Train & Fine-Tune Your AI Models

End-to-end ML training with LoRA/QLoRA fine-tuning, dataset management, model versioning, and cloud GPU provisioning. From data prep to production deployment.

Training Capabilities

Full-stack ML training infrastructure

LoRA & QLoRA Fine-Tuning

Fine-tune large language models efficiently with Low-Rank Adaptation. Reduce training costs by 90% compared to full fine-tuning.

Dataset Management

Organize training datasets by type: person re-ID, face recognition, agent feedback (RLHF), voice prints, object detection, and text classification.

Training Job Queue

BullMQ-powered job scheduling with progress tracking. Queue multiple training jobs with priority management.

Model Versioning

Track model versions, compare performance metrics, and roll back to previous versions with full lineage tracking.

A/B Testing & Canary

Deploy model versions side by side. Canary deployments with gradual traffic shifting based on performance metrics.

Cloud GPU Provisioning

One-click DigitalOcean GPU VM provisioning for training and inference. Automatic start/stop to minimize costs.

Train custom AI models

Fine-tune models on your data. Deploy to production with A/B testing and canary releases.

ML Training — Train ML Models | Lither