NeMo Data Designer is our core product from Gretel and now the internal framework we use heavily for both pre- and post-training data in Nemotron for a variety of use cases.
The OSS version is fully general-purpose: Python-first, modular, and designed so you can mix statistical samplers, LLM columns, and seed datasets in a single pipeline.
Happy to answer questions or hear feedback on missing features"},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["nvidia"],"value":"Nvidia open sources the synthetic data framework used to build Nemotron datasets"}},"_tags":["comment","author_alexwatson405","story_46136055"],"author":"alexwatson405","comment_text":"Hi all- I\u2019m a co-founder from Gretel; our team and tech are now part of NVIDIA.
NeMo Data Designer is our core product from Gretel and now the internal framework we use heavily for both pre- and post-training data in Nemotron for a variety of use cases.
The OSS version is fully general-purpose: Python-first, modular, and designed so you can mix statistical samplers, LLM columns, and seed datasets in a single pipeline.
Happy to answer questions or hear feedback on missing features","created_at":"2025-12-03T16:09:50Z","created_at_i":1764778190,"objectID":"46136161","parent_id":46136055,"story_id":46136055,"story_title":"Nvidia open sources the synthetic data framework used to build Nemotron datasets","updated_at":"2026-03-05T23:06:33Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"alexwatson405"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["data","designer","nvidia"],"value":"NVIDIA just open sourced NeMo Data Designer, the synthetic data framework used internally to build both pre-training and post-training datasets for Nemotron.
It lets you define an entire synthetic data pipeline directly in Python: structured outputs, statistical samplers, LLM-generated columns, dependency-aware field relationships, Python/SQL/remote validators, and optional LLM-as-judge scoring. Supports quick preview mode for fast iteration before scaling up.
Install:
```\npip install data-designer\n```
A minimal example:
```\nfrom data_designer.essentials import *
data_designer = DataDesigner()\nconfig = DataDesignerConfigBuilder()
config.add_column(\n SamplerColumnConfig(\n name="product_category",\n sampler_type=SamplerType.CATEGORY,\n params=CategorySamplerParams(\n values=["Electronics", "Clothing", "Home & Kitchen", "Books"]\n ),\n )\n)
config.add_column(\n LLMTextColumnConfig(\n name="review",\n model_alias="nvidia-text",\n prompt="Write a short product review for a {{ product_category }} item."\n )\n)
preview = data_designer.preview(config_builder=config)\npreview.display_sample_record()\n```
This release also incorporates the synthetic data tech my team originally built at Gretel (now part of NVIDIA), now generally available for anyone to use or extend.
Repo: https://github.com/NVIDIA-NeMo/DataDesigner"},"title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["nvidia"],"value":"Nvidia open sources the synthetic data framework used to build Nemotron datasets"}},"_tags":["story","author_alexwatson405","story_46136055","ask_hn"],"author":"alexwatson405","children":[46136161],"created_at":"2025-12-03T16:02:01Z","created_at_i":1764777721,"num_comments":1,"objectID":"46136055","points":8,"story_id":46136055,"story_text":"NVIDIA just open sourced NeMo Data Designer, the synthetic data framework used internally to build both pre-training and post-training datasets for Nemotron.
It lets you define an entire synthetic data pipeline directly in Python: structured outputs, statistical samplers, LLM-generated columns, dependency-aware field relationships, Python/SQL/remote validators, and optional LLM-as-judge scoring. Supports quick preview mode for fast iteration before scaling up.
Install:
```\npip install data-designer\n```
A minimal example:
```\nfrom data_designer.essentials import *
data_designer = DataDesigner()\nconfig = DataDesignerConfigBuilder()
config.add_column(\n SamplerColumnConfig(\n name="product_category",\n sampler_type=SamplerType.CATEGORY,\n params=CategorySamplerParams(\n values=["Electronics", "Clothing", "Home & Kitchen", "Books"]\n ),\n )\n)
config.add_column(\n LLMTextColumnConfig(\n name="review",\n model_alias="nvidia-text",\n prompt="Write a short product review for a {{ product_category }} item."\n )\n)
preview = data_designer.preview(config_builder=config)\npreview.display_sample_record()\n```
This release also incorporates the synthetic data tech my team originally built at Gretel (now part of NVIDIA), now generally available for anyone to use or extend.
Repo: https://github.com/NVIDIA-NeMo/DataDesigner","title":"Nvidia open sources the synthetic data framework used to build Nemotron datasets","updated_at":"2026-03-05T23:06:33Z"}],"hitsPerPage":20,"nbHits":2,"nbPages":1,"page":0,"params":"query=%22Data+Designer%22+NVIDIA&advancedSyntax=true&analyticsTags=backend","processingTimeMS":7,"processingTimingsMS":{"_request":{"roundTrip":25},"fetch":{"query":3,"scanning":2,"total":6},"total":7},"query":"\"Data Designer\" NVIDIA","serverTimeMS":8}