The CentML Platform simplifies deploying your custom models and AI applications. Package your model or application as a containerized HTTP server, then deploy it on CentML using the General Inference deployment option. Here’s an example of how to build a stable diffusion model served by a FastAPI-based inference server: https://github.com/CentML/codex/tree/main/general-apps/general-inference/stable-diffusion/centml-endpoint
By default, Docker containers run as the root user. However, the CentML Platform restricts running containers as root for security reasons. To address this, ensure that you create the container image using a non-root numeric user.Here’s an example of how you can configure this in a Dockerfile,
# Create a new user to run the application required for centml endpoints
ARG USERNAME="centml"
RUN useradd -u 1024 -m -d /home/${USERNAME} -s /bin/bash ${USERNAME} && chown -R ${USERNAME}:${USERNAME} /home/${USERNAME}
USER 1024
If you are building the container on MacOS, make sure to set the image platform as linux/amd64.
docker build --platform linux/amd64 -t stable-diffusion:latest .
After building the container, push it to a public container registry, such as Docker Hub. Then, navigate to the General Inference option in the CentML Platform and enter the image name, tag, and container port to deploy your application.

​
What’s Next

Agents on CentML

Learn how agents can interact with CentML services.

Clients

Learn how to interact with platform programmatically

Resources and Pricing

Learn more about CentML Pricing

Get Support

Submit a Support Request

CentML Serverless Endpoints

Dive deeper into advanced Serverless configurations and patterns.

LLM Serving

Explore dedicated public and private endpoints for production model and model infrastructure management.