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BentoML: A platform for serving and deploying machine learning models

• kevlar1818 7y ago
  The project's documentation gives a better overview of its capabilities: https://bentoml.readthedocs.io/en/latest/quickstart.html https://bentoml.readthedocs.io/en/latest/quickstart.html
  • chaoyu 7y ago
    Our quick start guide notebook on Google Colab is also a great place to get started! https://colab.research.google.com/github/bentoml/BentoML/blob/master/guides/quick-start/bentoml-quick-start-guide.ipynb https://colab.research.google.com/github/bentoml/BentoML/blo...
• suyash 7y ago
  Interesting project, I've heard a lot of good things about GraphPipe for Model Serving with support for multiple languages (Go, Python, Java) https://github.com/oracle/graphpipe https://github.com/oracle/graphpipe
  • chaoyu 7y ago
    Graphpipe solves a very unique problem when building ML model serving system, although BentoML is trying to solve a very different problem. We think it would be interesting to support GraphPipe's flatbuffer format in BentoML's REST API model server down the line if people are interested in that.
• chaoyu 7y ago
  Thanks for sharing the project Kevlar1818. BentoML author here - we are building BentoML to empower Data Scientists to ship prediction services instead of delivering "models" to dev teams. We proposed a workflow that made it easy for data scientists to create and test prediction services and then deploy them to cloud platforms such as AWS Lambda, SageMaker or Docker/Kubernetes. Happy to answer more questions, cheers!