#Nvidia-gpu
Showing 26 of 26 repositories tagged #nvidia-gpu, ranked by stars
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
Nvidia GPU exporter for prometheus using nvidia-smi binary
💰 USB flash drive ISO image for Ethereum, Zcash and Monero mining with NVIDIA graphics cards and Ubuntu GNU/Linux (headless)
Training/Fine-tuning at the speed of light
GPU environment and cluster management with LLM support
Docker Image for Ubuntu Desktop which support HW GPU accelerated GUI apps. you can access the Container with ssh or remote desktop, just like Cloud VM.
Multi-threaded GUI manager for mass creation of AI-generated art with support for multiple GPUs.
A consolidation of various compiled open-source AI image/video upscaling product for a working CLI friendly image and video upscaling program.
GPUd automates monitoring, diagnostics, and issue identification for GPUs
KDE Plasma Desktop container designed for Kubernetes, supporting OpenGL EGL and GLX, Vulkan, and Wine/Proton for NVIDIA GPUs through WebRTC and HTML5, providing an open-source remote cloud/HPC graphics or game streaming platform.
A shared library of on-demand DeepStream Pipeline Services for Python and C/C++
KDE Plasma Desktop container designed for Kubernetes, supporting OpenGL EGL and GLX, Vulkan, and Wine/Proton for NVIDIA GPUs through WebRTC and HTML5, providing an open-source remote cloud/HPC graphics or game streaming platform.
Securade.ai HUB - A generative AI based edge platform for computer vision that connects to existing CCTV cameras and makes them smart.
GPU-accelerated preview thumbnails for Plex, Emby & Jellyfin.
The inference engine the open-source world built for itself.
✨ 1-Click Free GPU on VS Code with Google Colab
Ubuntu 18.04 How to install Nvidia driver + CUDA + CUDNN + build tensorflow for gpu step by step command line
Solvers/annealers for simulated quantum annealing on CPU and CUDA(NVIDIA GPU).
PyProf2: PyTorch Profiling tool
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.
SORDI dataset has per frame annotation file in json format. Following tools create a COCO style annotation out of it. Thus the SORDI data can be easily fed into COCO style training pipelines.
Deep Reinforcement Learning applied to robotic arm
NVIDIA Falcon Microprocessor Suite
High-performance interactive system monitor for NVIDIA DGX systems — GPU, CPU, memory, disk, network in a beautiful TUI
Making data science and AI accessible
H.E.I.M.D.A.L.L looks at fleet telemetry and gives you natural-language insights. GPU data loading (cuDF), local LLM inference (Gemma 2), and production NIM on GKE. Open the notebooks, run cells, get answers! Quick start should not take longer than 10 minutes and the T4 path is completely free!