Deploying Deep Learning Models

Strategies to deploy deep learning models
Alternatives To Deploying Deep Learning Models
Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Ray29,596803632 months ago95December 04, 20233,528apache-2.0Python
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Gradio25,82312292 months ago534December 05, 2023452apache-2.0Python
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Paddlex4,51023 months ago54December 10, 2021538apache-2.0Python
PaddlePaddle End-to-End Development Toolkit(『飞桨』深度学习全流程开发工具)
Production Level Deep Learning3,957
4 months ago7
A guideline for building practical production-level deep learning systems to be deployed in real world applications.
Mmdeploy2,37122 months ago6September 22, 2023255apache-2.0Python
OpenMMLab Model Deployment Framework
Transformer Deploy1,542
5 months ago53apache-2.0Python
Efficient, scalable and enterprise-grade CPU/GPU inference server for 🤗 Hugging Face transformer models 🚀
Seldon Server1,420
4 years ago44June 28, 201726apache-2.0Java
Machine Learning Platform and Recommendation Engine built on Kubernetes
Keras Flask Deploy Webapp1,155
4 days agoapache-2.0JavaScript
:smiley_cat: Pretty & simple image classifier app template. Deploy your own trained model or pre-trained model (VGG, ResNet, Densenet) to a web app using Flask in 10 minutes.
Deep Learning In Production949
a year ago1Jupyter Notebook
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.
Now5882a year ago202September 20, 2023106apache-2.0Python
🧞 No-code tool for creating a neural search solution in minutes
Alternatives To Deploying Deep Learning Models
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