AI Agent Skills

Linux运维监控工具，支持系统硬件信息，内存，CPU，温度，磁盘空间及IO，硬盘smart，GPU，防火墙，网络流量速率等监控，服务接口监测，大屏展示，拓扑图，端口监控，进程监控，docker监控，日志监控，文件防篡改，数据库监控，指令批量下发执行，web ssh，Linux面板(探针)，告警，SNMP监测，K8S，Redis，Ngi…

Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model w/multiplatform CPU, AMD, NVIDIA GPU PyTorch support, handling, and auto-stitching

Modular ZK(Zero Knowledge) backend accelerated by GPU

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further e…

Run Keras models in the browser, with GPU support using WebGL

The NVIDIA VSS Blueprint is a suite of reference architectures for building GPU-accelerated vision agents and AI-powered video analytics applications.

AI 基础知识 - GPU 架构、CUDA 编程、大模型基础及AI Agent 相关知识。

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

GPU-accelerated force graph layout and rendering

Detect local hardware (RAM, CPU, GPU/VRAM) and recommend the best-fit local LLM models with optimal quantization, speed estimates, and fit scoring.

Workflow 1.5: Bridge between idea discovery and auto review. Reads EXPERIMENT_PLAN.md, implements experiment code, deploys to GPU, collects initial results. Use when use…

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <…

CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.

Build sharp, physically coherent high-resolution materials for 3D rendering with appropriate PBR maps, texel density, UV direction, mipmaps, anisotropic filtering, and p…

Read and write large cuPyNumeric arrays to HDF5 with Legate's parallel, distributed HDF5 I/O (legate.io.hdf5: to_file, from_file, from_file_batched). Use when a