Training# Training 5.1 Quick Start — CLI 5.2 Config-File Mode (Recommended) 5.3 All Hyperparameters Reference 5.4 Choosing an Encoder Multi-GPU Training Single Node, Multiple GPUs (most common setup) Single GPU How Distributed Training Works Multi-Node Multi-GPU (MNMG) — Slurm Advanced Training Options XGBoost Memory Modes Resuming Interrupted Training Monitoring Training Progress Class Imbalance and Calibration Hyperparameter Tuning Guidance Saving Node Embeddings for Hybrid Inference (EP Only) Automated Hyperparameter Optimisation — LLM Tuning + Grid Search Hyperparameter Tuning Guidance Phase 1 — LLM-Guided Iterative Tuning Phase 2 — Grid Search Recommended Two-Phase Workflow Running with Your Dataset — Single Node
