
BentoML: A platform for serving and deploying machine learning models - kevlar1818
https://github.com/bentoml/BentoML
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chaoyu
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!

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suyash
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)

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chaoyu
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.

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kevlar1818
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
Our quick start guide notebook on Google Colab is also a great place to get
started!

[https://colab.research.google.com/github/bentoml/BentoML/blo...](https://colab.research.google.com/github/bentoml/BentoML/blob/master/guides/quick-
start/bentoml-quick-start-guide.ipynb)

