A Tutorial for Serving Tensorflow Models using Kubernetes
APACHE-2.0 License
Project demonstrating dual model deployment scenarios using Vertex AI (GCP).
Create, train, and save Tensorflow Keras models all in Golang
Generic and easy-to-use serving service for machine learning models
This repository shows various ways of deploying a vision model (TensorFlow) from 🤗 Transformers.
A tutorial exploring multiple approaches to deploy a trained TensorFlow (or Keras) model or multi...
A flexible, high-performance serving system for machine learning models
Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlo...
In this repository, I will share some useful notes and references about deploying deep learning-b...
Code and files to go along with CS329s machine learning model deployment tutorial.
Winning Contribution of Michael Schwabe and David Lassig to BWI Data Analytics Hackathon 2020 in ...
Tutorial on running keras model in C++ and python tensorflow
TensorFlow as a Service, a general purpose framework to serve TF models.
This project shows how to serve an ONNX-optimized image classification model as a web service wit...
Standardized Serverless ML Inference Platform on Kubernetes
The TensorFlow Cloud repository provides APIs that will allow to easily go from debugging and tra...