A high-throughput and memory-efficient inference and serving engine for LLMs
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Updated
May 13, 2024 - Python
A high-throughput and memory-efficient inference and serving engine for LLMs
Standardized Serverless ML Inference Platform on Kubernetes
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.
The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
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.
A scalable inference server for models optimized with OpenVINO™
LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.
🏕️ Reproducible development environment
Hopsworks - Data-Intensive AI platform with a Feature Store
Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs
Python + Inference - Model Deployment library in Python. Simplest model inference server ever.
A scalable, high-performance serving system for federated learning models
FastAPI Skeleton App to serve machine learning models production-ready.
AICI: Prompts as (Wasm) Programs
Code samples for the Lightbend tutorial on writing microservices with Akka Streams, Kafka Streams, and Kafka
Model Deployment at Scale on Kubernetes 🦄️
The simplest way to serve AI/ML models in production
BentoML Example Projects 🎨
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
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