model-serving

A high-throughput and memory-efficient inference and serving engine for LLMs

The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes

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

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.

Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs

🚀 Awesome System for Machine Learning ⚡️ AI System Papers and Industry Practice. ⚡️ System for Machine Learning, LLM (Large Language Model), GenAI (Generative AI). 🍻 OSDI, NSDI, SIGCOMM, SoCC, MLSys, etc. 🗃️ Llama3, Mistral, etc. 🧑‍💻 Video Tutorials.

Olares: An Open-Source Personal Cloud to Reclaim Your Data

🏕️ Reproducible development environment

AICI: Prompts as (Wasm) Programs

MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.

Hopsworks - Data-Intensive AI platform with a Feature Store

High-performance inference framework for large language models, focusing on efficiency, flexibility, and availability.

An open source DevOps tool for packaging and versioning AI/ML models, datasets, code, and configuration into an OCI artifact.

The simplest way to serve AI/ML models in production

Community maintained hardware plugin for vLLM on Ascend

A highly optimized LLM inference acceleration engine for Llama and its variants.

A throughput-oriented high-performance serving framework for LLMs

A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine