project 07

RLHF Alignment Template

Full-stack solution for LLM alignment including RLHF training, reward model development, interactive feedback collection interface, model explainability dashboards, and scalable Kubernetes deployment.

Source

Python · PyTorch · RLHF · Docker · Kubernetes · SHAP

The problem

Aligning LLMs with human preferences requires complex infrastructure: reward modeling, feedback collection, training pipelines, and deployment - often built from scratch for each project.

The approach

Created a comprehensive template covering the full RLHF stack: data preprocessing, transfer learning, reinforcement learning implementation, web-based feedback collection, and production deployment with Kubernetes.

The outcome

Accelerates LLM alignment projects by providing battle-tested infrastructure for the complete RLHF workflow.

Architecture

Web UI (Feedback Collection) → Reward Model Training → RLHF Fine-tuning → Evaluation → Kubernetes Deployment

Key features

RLHF training pipeline with reward modeling
Transfer learning support for BERT, GPT, and other pre-trained models
Interactive web interface for human feedback collection
SHAP-based explainability dashboards for model transparency
Docker + Kubernetes deployment with auto-scaling (HPA)
Comprehensive evaluation metrics for alignment quality