Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
nemo-curator
nemo-curator is an open-source data skill for Claude Code and compatible agents, published by Orchestra-Research. Its author describes it as: “GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Sc…”. The project has 12k stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add Orchestra-Research/AI-Research-SKILLs`.
What nemo-curator does
NVIDIA's toolkit for preparing high-quality training data for LLMs.
Installation
Add nemo-curator to your agent with:
/plugin marketplace add Orchestra-Research/AI-Research-SKILLsAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
What's inside
The SKILL.md for nemo-curator is organised into these sections:
- When to use NeMo Curator
- Quick start
- Installation
- Basic text curation pipeline
- Data curation pipeline
- Stage 1: Quality filtering
- Stage 2: Deduplication
- Stage 3: PII redaction
- Stage 4: Classifier filtering
- GPU acceleration
- GPU vs CPU performance
- Multi-GPU scaling
When to use it
Reach for nemo-curator when you want data help from your agent without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Ships in Orchestra-Research/AI-Research-SKILLs, an established project with 11,807 GitHub stars
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does nemo-curator do?
- GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
- How do I install nemo-curator?
- Run /plugin marketplace add Orchestra-Research/AI-Research-SKILLs in your agent, then reload your skills. Review the source at https://github.com/Orchestra-Research/AI-Research-SKILLs before installing.
- Is nemo-curator free to use?
- Yes. nemo-curator is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Where does nemo-curator come from?
- nemo-curator ships inside Orchestra-Research/AI-Research-SKILLs, a repository that contains 41 catalogued skills in total. The repository's 11,807 GitHub stars apply to that whole collection, not to this skill on its own.
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