Nine-chapter course teaching prompt engineering for Claude: from basic prompt structure through roles, output formatting, and hallucination control to complete prompts for chatbot, legal, finance, and coding tasks. Runs as editable Jupyter notebooks.
Hands-on coding tutorial series for large language models with slides and runnable notebooks covering fine-tuning, prompting, RLHF, safety, steganography, watermarking, multimodal models, GUI agents, and deployment. Community-maintained, free course materials for students and researchers.
A minimal GPU written in under 15 SystemVerilog files to teach how GPUs execute parallel kernels from the ground up. Includes an 11-instruction ISA, multiple cores with ALUs and load-store units, a fetch-decode-execute pipeline, and matrix kernels.
Runs a privacy-first, self-hosted answering engine that combines web retrieval with local and cloud LLMs to produce cited answers. Supports SearxNG search, file uploads, image/video search, and mix-and-match models with Speed/Balanced/Quality modes.
An MCP server giving Claude and other AI assistants direct control of the local terminal and file system: run shell commands, manage long-running processes, and search and diff-edit files across the whole OS, not just one project folder.
Turns any website into clean markdown, structured JSON, or screenshots through a single API — handling JavaScript rendering, rotating proxies, rate limits, and full-site crawling so LLM apps get web data without running scraping infrastructure.
Provides local inference, fine-tuning, and a server/CLI for vision–language and omni (image/audio/video) models via MLX. Supports multi-image chat, audio/video inputs, activation quantization (CUDA), TurboQuant KV cache, and LoRA/QLoRA fine-tuning for on-device workflows.
Chains pre-trained AI weather and climate models like GraphCast, Pangu, and FourCastNet into composable inference pipelines. Swap prognostic or diagnostic components, plug in reanalysis sources, and add ensemble perturbations or in-loop metrics.
Accelerates video generation with a unified framework for inference, finetuning, LoRA, distillation, sparse attention, and distributed execution for research and demos.
React components for building LLM chat and agent interfaces: message bubbles, prompt sets, conversation lists, and sender inputs under a RICH interaction paradigm, plus a streaming Markdown renderer and hooks for wiring UI to model data streams.
Runs reproducible evaluations of large language models through a Python API with built-in solvers, scorers, and model-graded grading. Ships 200+ ready-to-run evals spanning capability and safety testing, and connects to most major model providers.
Web-based resume editor with real-time preview, custom themes, dark mode, auto-save and PDF export, plus built-in AI-assisted writing and a custom model for polishing content. Open-source under Apache-2.0 but requires a commercial license for paid/enterprise use.