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What is Truss?

It is a seamless bridge from model development to model delivery. Truss presents an open-source standard for packaging models built in any framework for sharing and deployment in any environment, local or production.
Truss is a tool in the Machine Learning Tools category of a tech stack.
Truss is an open source tool with 697 GitHub stars and 40 GitHub forks. Here’s a link to Truss's open source repository on GitHub

Truss Integrations

Python, TensorFlow, PyTorch, scikit-learn, and MLflow are some of the popular tools that integrate with Truss. Here's a list of all 6 tools that integrate with Truss.

Truss's Features

  • Turns your Python model into a microservice with a production-ready API endpoint, no need for Flask or Django
  • For most popular frameworks, includes automatic model serialization and deserialization
  • Freezes dependencies via Docker to make your training environment portable
  • Enables rapid iteration with local development that matches your production environment
  • Encourages shipping parsing and even business logic alongside your model with integrated pre- and post-processing functions
  • Bundles secret management to securely give your model access to API keys

Truss Alternatives & Comparisons

What are some alternatives to Truss?
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
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Related Comparisons
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