5 boosters for "cuda" — open source, verified from GitHub, ready to install
Rules and patterns for ML demos on Hugging Face Spaces with ZeroGPU hardware. Covers , duration and quota tuning, process isolation, the CUDA availability model, concurrency safety, and CUDA build constraints. This skill is for Gradio SDK Spaces using ZeroGPU hardware. Docker and Static Spaces canno
Search the Hugging Face Hub for llama.cpp-compatible GGUF repos, choose the right quant, and launch the model with or . 1. Search the Hub with . 3. Prefer the exact HF local-app snippet and quant recommendation when it is visible.
Drive a profile → modify → benchmark → log → commit loop on a GPU kernel until it runs faster than the reference. The user provides at minimum a kernel; everything else (reference, inputs, bench script, hints) is optional. Does NOT apply when: Before doing anything else, establish the workspace — th
Query a structured, cross-referenced knowledge base of GPU kernel optimization for NVIDIA Blackwell (SM100) and Hopper (SM90). The repository update date is recorded in ; run for current corpus counts. Trigger this skill when the user asks about: Do NOT use this skill for:
"name": "cppcheatsheet", "description": "Comprehensive C/C++ programming reference covering modern C11-C23, C++11-C++23, system programming, CUDA GPU computing, debugging tools, Rust interop, and advanced topics", "name": "crazyguitar"
