{"schema_version":"onlylabs.public_signal.v1","title":"NVIDIA Repo: NVIDIA/structured-data-models-client","description":"NVIDIA repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/5ffe84b7-3b47-420b-a7bd-6b0cc746afb1","json_url":"https://onlylabs.fyi/signals/5ffe84b7-3b47-420b-a7bd-6b0cc746afb1/signal.json","generated_at":"2026-10-24T20:22:21.531Z","evidence_latest_fetched_at":"2026-10-16T07:04:04.222078+00:00","signal_first_seen_at":"2026-10-16T07:00:42.373998+00:00","org":{"slug":"nvidia","name":"NVIDIA","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/nvidia","dossier_json_url":"https://onlylabs.fyi/labs/nvidia/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/5ffe84b7-3b47-420b-a7bd-6b0cc746afb1","signal_json":"https://onlylabs.fyi/signals/5ffe84b7-3b47-420b-a7bd-6b0cc746afb1/signal.json","source":"https://github.com/NVIDIA/structured-data-models-client","lab_dossier":"https://onlylabs.fyi/labs/nvidia","lab_dossier_json":"https://onlylabs.fyi/labs/nvidia/dossier.json","analysis":"https://onlylabs.fyi/analysis/nvidia","analysis_json":"https://onlylabs.fyi/analysis/nvidia/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/nvidia/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"data","label":"Data demand","url":"https://onlylabs.fyi/data-radar/data","json_url":"https://onlylabs.fyi/data-radar/data/signals.json"},{"key":"infrastructure","label":"Infrastructure","url":"https://onlylabs.fyi/data-radar/infrastructure","json_url":"https://onlylabs.fyi/data-radar/infrastructure/signals.json"}]}},"answer_pack":{"answer":"NVIDIA published NVIDIA/structured-data-models-client (Python). 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Language: Python License: Apache-2.0 Stars: 1 Forks: 0 Open issues: 3 Created: 2026-10-06T04:05:18Z Pushed: 2026-10-16T05:32:04Z Default branch: main Fork: no Archived: no README: NVIDIA Structured Data Models Client Ask a predictive question of one table, or of a whole relational schema, and get an answer without training a model for each dataset. ```bash pip install 'structured-data-models-client[relational]' ``` Overview Structured-data foundation models predict in context. You give the model labelled rows and the rows you want scored, and it answers in one pass. There is no training loop, no hyperparameter search, and no per-dataset artifact to manage. This client talks to those models. It builds the request, sends it to a NIM inference endpoint, and gives you back a `PredictionResult`, which `to_pandas()` turns into a DataFrame. Inference runs in the NIM, so this package downloads no weights and needs no GPU. 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