serving

#大语言模型#Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

#计算机科学#A flexible, high-performance serving system for machine learning models

#搜索#AI + Data, online. https://vespa.ai

#计算机科学#A Cloud Native Batch System (Project under CNCF)

#计算机科学#An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

#计算机科学#In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

#计算机科学#TorchServe是一个高性能、灵活且易于使用的工具，用于在生产级环境中提供PyTorch模型的服务。

#计算机科学#The easiest way to deploy agents, MCP servers, models, RAG, pipelines and more. No MLOps. No YAML.

#大语言模型#High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle

#大语言模型#Database system for AI-powered apps

#大语言模型#A course of learning LLM inference serving on Apple Silicon for systems engineers.

#计算机科学#TensorFlow template application for deep learning

#计算机科学#A comprehensive guide to building RAG-based LLM applications for production.

#前端开发#DELTA is a deep learning based natural language and speech processing platform. LF AI & DATA Projects: https://lfaidata.foundation/projects/delta/

A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ...

#计算机科学#A flexible, high-performance carrier for machine learning models（『飞桨』服务化部署框架）

#计算机科学#Generic and easy-to-use serving service for machine learning models

#计算机科学#A scalable inference server for models optimized with OpenVINO™

#自然语言处理#Python + Inference - Model Deployment library in Python. Simplest model inference server ever.

A unified end-to-end machine intelligence platform