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NVIDIA/DeepLearningExamples

NVIDIA / DeepLearningExamples

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State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

14.9kstars
3.4kforks
321open issues
2024-08-12last pushed
Unknownlicense

What it is, and how people use it

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure. It sits on the Dev Agents & Programs shelf of the catalog, maintained by @NVIDIA.

✓Drop-in for Claude Code, Codex CLI and Cursor - install and it just runs.
✓Read the SKILL.md / README first; most setups are one command from the docs.
✓Teams use it to standardise how agents behave across every repo in the org.
computer-visiondeep-learningdrug-discoveryforecastinglarge-language-models

Why builders keep it installedDev Agents & Programs benefits

Day-one leverage

These CLIs and dashboards solve one job well and install with a single command. Value shows up in the first hour, not after a config weekend.

Composes with your agent

Most of them ship an MCP server, skill or hooks - so the same tool you use manually becomes an action your agent can call safely.

Built under real workloads

Star counts here track repos people actually run daily: the issue history shows bug classes fixed under production pressure, not demo-week polish.

Free and open source

Every tool on this page ships under an open license and can be self-hosted. Your usage data and your configs stay yours.

Contributorsloading from GitHub…

NVNVIDIdev1370NVNVIDIdev2333NVNVIDIdev3296NVNVIDIdev4259NVNVIDIdev5222NVNVIDIdev6185NVNVIDIdev7148NVNVIDIdev8111

Languagesestimated from snapshot

  • Jupyter Notebook 87.9%
  • Shell 12.1%

Community pulsesnapshot ratios, normalized

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