1313 Python Model-sparsification Libraries

Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Yolov5 running on TorchServe (GPU compatible) ! This is a dockerfile to run TorchServe for Yolo v5 object detection model. (TorchServe (PyTorch librar

82 Nov 29, 2022

Repository to run object detection on a model trained on an autonomous driving dataset.

Autonomous Driving Object Detection on the Raspberry Pi 4 Description of Repository This repository contains code and instructions to configure the ne

51 Nov 17, 2022

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Welcome to TensorWatch TensorWatch is a debugging and visualization tool designed for data science, deep learning and reinforcement learning from Micr

3.3k Dec 27, 2022

A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:

A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s

285 Jan 2, 2023

Create UIs for prototyping your machine learning model in 3 minutes

Note: We just launched Hosted, where anyone can upload their interface for permanent hosting. Check it out! Welcome to Gradio Quickly create customiza

11.7k Jan 7, 2023

Model Serving Made Easy

The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework

4.4k Jan 8, 2023

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

3k Jan 3, 2023

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

Regularized Greedy Forest Regularized Greedy Forest (RGF) is a tree ensemble machine learning method described in this paper. RGF can deliver better r

364 Dec 28, 2022

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

23.2k Dec 30, 2022

Python Model-sparsification Resources

Python model-sparsification Libraries

Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Repository to run object detection on a model trained on an autonomous driving dataset.

Debugging, monitoring and visualization for Python Machine Learning and Data Science

A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:

Create UIs for prototyping your machine learning model in 3 minutes

Model Serving Made Easy

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Model serving at scale

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Quickly and easily create / train a custom DeepDream model

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

Python Model-sparsification Resources

Python model-sparsification Libraries

Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready inference.

Repository to run object detection on a model trained on an autonomous driving dataset.

Debugging, monitoring and visualization for Python Machine Learning and Data Science

A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:

Create UIs for prototyping your machine learning model in 3 minutes

Model Serving Made Easy

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

Model serving at scale

Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)

Quickly and easily create / train a custom DeepDream model

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

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