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May 28, 2020
#
model-serving
Here are 37 public repositories matching this topic...
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
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deanwampler
commented
Feb 20, 2018
Either a data/README file or put a section in the ./README. People will want to know where we got the data (and we have to be careful to use data that might have restrictive licenses).
ravwojdyla
commented
Jul 12, 2018
Apply consequences of spotify/scio#1238:
- inference on local models should be by default sync
- inference on remote models (ml-engine) should be async by default
spi-x-i
opened
Sep 22, 2017
Code and presentation for Strata Model Serving tutorial
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Sep 26, 2019 - Scala
A scalable, high-performance serving system for federated learning models
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Jun 6, 2020 - Java
An umbrella project for multiple implementations of model serving
kafka
akka-http
tensorflow
spark-streaming
akka-streams
pmml
flink
kafka-streams
spark-ml
model-serving
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Sep 18, 2017 - Scala
FastAPI Skeleton App to serve machine learning models production-ready.
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Feb 15, 2020 - Python
mlserve turns your python models into RESTful API, serves web page with form generated to match your input data.
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Dec 28, 2019 - Python
Generic Model Serving Implementation leveraging Flink
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Jan 3, 2019 - Java
AkshatBajaj
commented
Mar 23, 2020
@zacbrannelly Not sure if this is possible in the current released version, so creating this just to keep track.
Kubeflow example of machine learning/model serving
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Jan 11, 2020 - Jupyter Notebook
BentoML Example Projects Gallery
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bentoml
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Jun 2, 2020 - Jupyter Notebook
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Titus 2 : Portable Format for Analytics (PFA) implementation for Python 3.4+
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titus
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Apr 19, 2020 - Python
Deploy DL/ ML inference pipelines with minimal extra code.
docker
deep-learning
gunicorn
pytorch
falcon
http-server
gevent
tensorflow-serving
model-deployment
model-serving
serving
tf-serving
torchserve
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May 16, 2020 - Python
Speculative model serving with Flink
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Sep 24, 2018 - Scala
Serving the deep learning models easily.
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May 27, 2020 - Python
Experimental implementation of speculative model serving
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May 30, 2019 - Scala
Machine learning logistics and serving platform
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May 19, 2020 - JavaScript
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Nov 19, 2018 - Scala
Tensorflow Serving with Docker / Docker Compose
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flask
protobuf
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tensorflow
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protos
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Jan 27, 2020 - Python
Serving layer for large machine learning models on Apache Flink
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Aug 8, 2018 - Java
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When serving the model locally, a nice swagger documentation page becomes accessible that allows you to send requests to the model by clicking the "Try it out" button.
As part of the swagger specification it is possible to specify the schema the endpoint expects. When doing that, the "Try it out" button will be prefilled with values, so that the API end users can experiment with the endpoint more