About COG

COG is an open-source tool designed to package machine learning models into standard, production-ready containers. It simplifies the process of deploying machine learning models, whether on your own infrastructure or on Replicate.

Here are four key features of COG

  1. Simplified Docker Containers: COG simplifies the process of creating Docker containers for machine learning models. It uses a simple configuration file to define your environment and generates a Docker image incorporating best practices.
  2. CUDA Compatibility: COG understands the compatibility between different versions of CUDA, cuDNN, PyTorch, Tensorflow, and Python, and sets them up correctly for you, eliminating the complexities of managing these dependencies.
  3. Standard Python Inputs and Outputs: With COG, you can define the inputs and outputs for your model using standard Python. COG then generates an OpenAPI schema and validates the inputs and outputs with Pydantic.
  4. Automatic HTTP Prediction Server: COG uses your model’s types to dynamically generate a RESTful HTTP API using FastAPI. This allows for easy integration of your model into web applications and services.