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synthetic-data Skill

AI Agent SkillPythonOpen source

Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines Published by microsoft in physical-ai-toolchain.

What is synthetic-data Skill?

Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines Published by microsoft in physical-ai-toolchain. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
49/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use synthetic-data Skill

  • Use it for data analysis.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/physical-ai-toolchain
  • Skill file: .github/skills/synthetic-data/SKILL.md

What it does

Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines

Skill instructions

Synthetic Data Skill Generate photorealistic training data using NVIDIA Cosmos world foundation models — Cosmos Transfer, Cosmos Predict, and Cosmos Reason. Overview The Synthetic Data domain provides SDG pipelines that transform simulation-rendered frames into photorealistic training data, predict future environment states, and curate output for training quality. Pipeline Stages | Stage | Model | Purpose | |-------|-------|---------| | Transfer | Cosmos Transfer 2.5 | Convert Isaac Sim renders to photorealistic images | | Predict | Cosmos Predict 2.5 | Generate future frame sequences from observations | | Reason | Cosmos Reason 2 | Assess data quality and filter training samples | Workflow Submission SDG workflows can be submitted via OSMO or AzureML: - OSMO workflows: synthetic-data/workflows/osmo/ - AzureML jobs: synthetic-data/workflows/azureml/ Key Files | File | Purpose | |------|---------| | synthetic-data/README.md | Domain overview and directory structure | | synthetic-data/wo

Explore related resources

Frequently asked questions

What is synthetic-data?

synthetic-data is a open-source AI agent skill with Copy skill directory. Generate synthetic training data using NVIDIA Cosmos world foundation models for SDG pipelines

Who is synthetic-data best for?

synthetic-data is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install synthetic-data?

Install or run synthetic-data using Copy skill directory. Check synthetic-data for the latest setup command.

Is synthetic-data actively maintained?

synthetic-data may need a closer maintenance check before production use.

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Stars
94
Forks
48
Last commit
9 days ago
Repository age
5 months
License
MIT

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