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- nvidia.com
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- DeepLearningExamples
DeepLearningExamples PublicState-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
- open-gpu-kernel-modules
open-gpu-kernel-modules PublicNVIDIA Linux open GPU kernel module source
- nvidia-container-toolkit
nvidia-container-toolkit PublicBuild and run containers leveraging NVIDIA GPUs
- GenerativeAIExamples
GenerativeAIExamples PublicGenerative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
Repositories
- TransformerEngine Public
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
NVIDIA/TransformerEngine’s past year of commit activity - nvidia-resiliency-ext Public
NVIDIA Resiliency Extension is a python package for framework developers and users to implement fault-tolerant features. It improves the effective training time by minimizing the downtime due to failures and interruptions.
NVIDIA/nvidia-resiliency-ext’s past year of commit activity - NeMo Public
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
NVIDIA/NeMo’s past year of commit activity - gpu-driver-container Public
The NVIDIA GPU driver container allows the provisioning of the NVIDIA driver through the use of containers.
NVIDIA/gpu-driver-container’s past year of commit activity - kata-containers Public Forked fromkata-containers/kata-containers
Kata containers is an implementation of lightweight Virtual Machines (VMs) that feel and perform like containers, but provide the workload isolation and security advantages of VMs.
NVIDIA/kata-containers’s past year of commit activity - nv-ingest Public
NVIDIA Ingest is an early access set of microservices for parsing hundreds of thousands of complex, messy unstructured PDFs and other enterprise documents into metadata and text to embed into retrieval systems.
NVIDIA/nv-ingest’s past year of commit activity