Customizing Models
===================

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   <div class="v3-exclusive-feature">
   <strong>🆕 V3 EXCLUSIVE FEATURE</strong><br>
   Model customization with specialized trainers is available only in SageMaker Python SDK V3, built from the ground up for foundation model fine-tuning.
   It streamlines the complex process of customizing AI models from months to days with a guided UI and serverless infrastructure that removes operational overhead. Whether you are building legal research applications, customer service chatbots, or domain-specific AI agents, this feature accelerates your path from proof-of-concept to production deployment.
   </div>

Key Benefits
-------------

* **Serverless Training**: Fully managed compute infrastructure that abstracts away all infrastructure complexity, allowing you to focus purely on model development
* **Advanced Customization Techniques**: Comprehensive set of methods including supervised fine-tuning (SFT), direct preference optimization (DPO), reinforcement learning with verifiable rewards (RLVR), and reinforcement learning with AI feedback (RLAIF)
* **AI Model Customization Assets**: Integrated datasets and evaluators for training, refining, and evaluating custom models
* **Production Ready**: Built-in evaluation, monitoring, and deployment capabilities with automatic resource management

.. toctree::
   :maxdepth: 2

   open_weight_model_customization
   nova
   evaluation
   deployment