A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.

NVIDIA NCCL Tests for Distributed Training

Tools for extracting features of floodplain topography relevant to channel-routing.

A collection of Dockerfiles and Singularity deffiles for Pawsey-supported images

Making large AI models cheaper, faster and more accessible

Keep searching, reading webpages, reasoning until it finds the answer (or exceeding the token budget)

Task scheduling library for Python

Deep Learning at Scale Training Event at NERSC

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 retri…

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

Read and write TIFF files.

⏩ Create, share, and use custom AI code assistants with our open-source IDE extensions and hub of models, rules, prompts, docs, and other building blocks

High throughput workflows and automation for HPC

ECMWF's workflow manager

A linter for xarray datasets

[NAACL'24] Dataset, code and models for "TableLlama: Towards Open Large Generalist Models for Tables".

🤗 smolagents: a barebones library for agents. Agents write python code to call tools and orchestrate other agents.

A SwiftUI based macOS GUI for rsync.

PANGAEA Python Client

ExactPack: An Open-Source Software Package for Code Verification

Editorial venue for ML Reproducibility Challenge Accepted papers

High accuracy RAG for answering questions from scientific documents with citations

The fastest knowledge base for growing teams. Beautiful, realtime collaborative, feature packed, and markdown compatible.

Adaptation of PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations for emulating high resolution climate models

NVIDIA Data Center GPU Manager (DCGM) is a project for gathering telemetry and measuring the health of NVIDIA GPUs

Sources for the Oak Ridge Leadership Computing Facility User Documentation

Visualize machine learning models with Netron in VSCode