Model Lifecycle

Overview

Production models do not end with a single deployment. This section covers all stages of the model lifecycle, from custom model deployment and LoRA fine-tuning pipelines to MLOps orchestration (Kubeflow/Argo) and Continuous Training (GRPO/DPO/Canary rollout).

Documents

📄️ Model Deployment

Hands-on guide to deploying large open-source models on EKS, based on the GLM-5.1 experience

📄️ Custom Model Pipeline

Building a domain-optimized model serving pipeline with LoRA Fine-tuning, Multi-LoRA Hot-swap, and SLM Cascade Routing

📄️ MLOps Pipeline

End-to-end ML lifecycle management with Kubeflow + MLflow + vLLM + ArgoCD GitOps

🗃️ Continuous Training

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