Use cases
Baseten Training provides a robust, scalable, and configurable platform for:- Training machine learning models efficiently.
- Managing training artifacts, such as model checkpoints and logs.
- Seamlessly productionize trained models to scalable deployments.
Benefits of using Baseten training
Leveraging Baseten Training for your model training workflows offers several key advantages:- Reproducibility: Ensure consistent training runs by precisely defining your environment, code, and configurations.
- Scalability: Easily scale your training jobs from single-node to multi-node distributed training to handle large datasets and complex models.
- Simplified Management: Organize, monitor, and manage your training projects and jobs in a centralized platform.
- Resource Flexibility: Configure compute resources (CPU, GPU, memory) tailored to the specific needs of each training job.
- Integrated Workflow: Transition from training to inference and evals seamlessly within the Baseten ecosystem.
- Artifact Management: Handle large artifacts like models, checkpoints, and datasets efficiently with Baseten storage.
- Framework Agnostic: Bring your favorite training framework or roll your own with Baseten’s framework-agnostic training API.