Starred repositories
Tooling for optimized, validated, and reproducible GPU-accelerated AI runtime in Kubernetes
DSPy: The framework for programming—not prompting—language models
GPU Cluster Monitoring (GCM): Large-Scale AI Research Cluster Monitoring
280+ free n8n automation templates — ready-to-use workflows for Gmail, Telegram, Slack, Discord, WhatsApp, Google Drive, Notion, OpenAI, and more. AI agents, RAG chatbots, email automation, social …
Crawl a site to generate knowledge files to create your own custom GPT from a URL
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama mode…
All the resources you need to get to Senior Engineer and beyond
📚 Find your next book to read!
Curated coding interview preparation materials for busy software engineers
Kubernetes-native platform to run massively parallel data/streaming jobs
The fastai book, published as Jupyter Notebooks
Solve puzzles. Improve your pytorch.
High-performance, asynchronous Python HTTP client library designed for faster file transfers using concurrency, semaphores, and fault-tolerant features.
A toolkit to run Ray applications on Kubernetes
High-performance In-browser LLM Inference Engine
A framework for serving and evaluating LLM routers - save LLM costs without compromising quality
A curated list of awesome projects and resources related to Argo (a CNCF graduated project)
⚡ Flash Diffusion ⚡: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation (AAAI 2025 Oral)
AI Inference Operator for Kubernetes. The easiest way to serve ML models in production. Supports VLMs, LLMs, embeddings, and speech-to-text.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python SDK, Proxy Server (AI Gateway) to call 100+ LLM APIs in OpenAI (or native) format, with cost tracking, guardrails, loadbalancing and logging. [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthr…
Lab Materials for MIT 6.S191: Introduction to Deep Learning
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`
Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas - Effortless optimization at its finest!