AI Model Customization Job Submission

SageMaker Python SDK V3 provides four specialized trainer classes for different model customization approaches:

SFTTrainer (Supervised Fine-Tuning)

Traditional fine-tuning with labeled datasets for task-specific adaptation

DPOTrainer (Direct Preference Optimization)

Fine-tune models using human preference data without reinforcement learning complexity

RLAIFTrainer (Reinforcement Learning from AI Feedback)

Use AI-generated feedback to improve model behavior and alignment

RLVRTrainer (Reinforcement Learning from Verifiable Rewards)

Fine-tune with verifiable reward signals for objective optimization