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Why Truss?

  • Write once, run anywhere: Package and test model code, weights, and dependencies with a model server that behaves the same in development and production.
  • Fast developer loop: Implement your model with fast feedback from a live reload server, and skip Docker and Kubernetes configuration with a batteries-included model serving environment.
  • Support for all Python frameworks: From transformers and diffusers to PyTorch and Tensorflow to XGBoost and sklearn, Truss supports models created with any framework, even entirely custom models.

See Trusses for popular models including:

and dozens more examples on GitHub.

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Deploy your first model

Quickstart

Package, deploy, and invoke an ML model in production all in less than five minutes.

Truss tutorial

Learn model deployment step-by-step from “Hello, World!” to streaming output from an open-source LLM.

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Truss contributors

Truss is backed by Baseten and built in collaboration with ML engineers worldwide. Special thanks to Stephan Auerhahn @ stability.ai and Daniel Sarfati @ Salad Technologies for their contributions.

We enthusiastically welcome contributions in accordance with our contributors’ guide and code of conduct.

Quickstart