MNN
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba (by alibaba)
serving
A flexible, high-performance serving system for machine learning models (by tensorflow)
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
MNN
Posts with mentions or reviews of MNN.
We have used some of these posts to build our list of alternatives
and similar projects.
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Newbie having error code of cannot build selected target abi x86 no suitable splits configured
I found a solution on GitHub check your app's build.gradle, defaultConfig section - you need to add x86 to your ndk abiFilters ndk.abiFilters 'armeabi-v7a','arm64-v8a', 'x86' GitHub Hope it will help. You have to find that file and edit it as given here
serving
Posts with mentions or reviews of serving.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-16.
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Popular Machine Learning Deployment Tools
GitHub
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If data science uses a lot of computational power, then why is python the most used programming language?
You serve models via https://www.tensorflow.org/tfx/guide/serving which is written entirely in C++ (https://github.com/tensorflow/serving/tree/master/tensorflow_serving/model_servers), no Python on the serving path or in the shipped product.
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Running concurrent inference processes in Flask or should I use FastAPI?
Don't roll this yourself. Look at Tensorflow Serving: https://github.com/tensorflow/serving.
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Exposing Tensorflow Serving’s gRPC Endpoints on Amazon EKS
gRPC only connects to a host and port — but we can use whatever service route we want. Above I use the path we configured in our k8s ingress object: /service1, and overwrite the base configuration provided by tensorflow serving. When we call the tfserving_metadata function above, we specify /service1 as an argument.
What are some alternatives?
When comparing MNN and serving you can also consider the following projects:
tensorflow - An Open Source Machine Learning Framework for Everyone
flashlight - A C++ standalone library for machine learning
oneflow - OneFlow is a performance-centered and open-source deep learning framework.
OpenMLDB - OpenMLDB is an open-source machine learning database that provides a feature platform enabling consistent features for training and inference.
ML-examples - Arm Machine Learning tutorials and examples