Cerebrium

Cerebrium is a platform that enables users to easily and efficiently construct, deploy, and monitor machine learning models using just a few lines of code. It provides a simplified machine learning framework that streamlines the process of training, deploying, and monitoring models, eliminating the need for extensive coding knowledge.

With Cerebrium, users can effortlessly deploy serverless GPU models using popular ML frameworks like PyTorch, ONNX, and XGBoost with just one line of code. The tool also supports the deployment of prebuilt models optimized for sub-second latency, making it ideal for real-time applications.

In addition to model deployment, Cerebrium offers support for custom model deployments, allowing users to connect multiple custom models to create unique functionality. It also provides automatic versioning and rollback options, simplifying the management of different model versions.

Cerebrium simplifies the training process with its fine-tuning feature, which enables users to optimize smaller models for specific tasks, reducing costs and latency while improving performance. The tool also supports the use of open-source models like GPT-Neo and Stable Diffusion, providing alternatives to proprietary models such as GPT-3.

Monitoring models is made easy with Cerebrium, as it integrates seamlessly with leading ML observability platforms like Arize and Censius. This integration allows users to receive alerts for prediction drift and compare different model versions, facilitating quick issue resolution. Cerebrium is trusted by teams at Twilio, Ramp, and Writesonic.