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vCluster creates tenant clusters: fully isolated environments delivered as managed Kubernetes, or as the foundation for Slurm, Ray, Run:ai and inference clusters. Each gets its own API server, CRDs and RBAC, and runs on an existing cluster or standalone on bare metal. CNCF Certified Kubernetes.
TranslatedOpen-source manuscript of 《深入理解 AI Infra：量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
Generate Nix packages from URLs with hash prefetching, dependency inference, license detection, and more [maintainer=@figsoda]
This repository provides you with an easy-to-use labeling tool for State-of-the-art Deep Learning training purposes. It supports Auto-Labeling.
Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.
⚡ Open-source software for deep learning-based digital pathology