replicate/cog

Health v2 · maintenance only

Adoption not part of the score

9463 stars · 696 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Cog is an open-source CLI tool that packages machine learning models into production-ready Docker containers using a simple cog.yaml configuration and a Python run interface. It automatically resolves CUDA/cuDNN/framework compatibility, generates an OpenAPI schema, and serves the model via an auto-generated HTTP inference API.

Use cases

• package a machine learning model into a docker container
• avoid writing dockerfiles and fixing cuda version conflicts for pytorch models
• serve a model behind a rest http api
• deploy a trained model to my own gpu infrastructure
• run model inference in a reproducible environment
• build a container image for a model to deploy anywhere docker runs
• define model inputs and outputs with python type hints

When to choose

• you want to containerize PyTorch or TensorFlow models without hand-writing Dockerfiles
• you need a standard, reproducible way to package and serve ML models
• you want an automatic HTTP inference server with input validation
• you plan to deploy models to Replicate or any Docker-capable host

When to avoid

• you need to serve non-ML web applications rather than models
• you don't use Docker or can't run containers on your infrastructure
• you need a lightweight solution without container overhead
• your models aren't in Python

Facets

cli-tool · maturity active

machine-learning deployment container-runtime http-server api-framework developer-tools machine-learning deep-learning developer-tools windows cli python go docker cuda gpu pytorch tensorflow model-packaging inference-server openapi replicate containers devops linux macos

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markdown · JSON · MCP: product_card(name="replicate/cog")