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Run your own AI cluster at home with everyday devices 📱💻 🖥️⌚
User-friendly WebUI for LLMs (Formerly Ollama WebUI)
Agentic components of the Llama Stack APIs
SDKs for a variety of languages and platforms that help connect devices to Microsoft Azure IoT services
Go modular http middleware to measure HTTP requests independent of metrics backend (with Prometheus and OpenCensus as backend implementations) and http framework/library
Stable Diffusion with Core ML on Apple Silicon
Example applications using the onnxruntime_go library.
Collaborative book Machine Learning Systems
FastMLX is a high performance production ready API to host MLX models.
This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) avai…
Official implementation of "Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling"
Video+code lecture on building nanoGPT from scratch
Use any web browser or WebView as GUI, with your preferred language in the backend and modern web technologies in the frontend, all in a lightweight portable library.
Use any web browser as GUI, with Go in the backend and modern web technologies in the frontend.
NixOS Guide. Learn all about the immutable Nix Operating System and the declarative Nix Expression Language.
a research paper for generative cartoon interpolation
Phi-3 for Mac: Locally-run Vision and Language Models for Apple Silicon
mactop - Apple Silicon Monitor Top written in pure Golang! Under 1,000 lines of code.
Borgo is a statically typed language that compiles to Go.
Large Language Models (LLMs) applications and tools running on Apple Silicon in real-time with Apple MLX.
Schedule-Free Optimization in PyTorch
OpenUI let's you describe UI using your imagination, then see it rendered live.
Cross-platform Bluetooth API for Go and TinyGo. Supports Linux, macOS, Windows, and bare metal using Nordic SoftDevice or HCI
To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
Tutorial for libSDL2pp, C++11 bindings/wrapper for SDL2