Build your own benchmark feature integration #174
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Signed-off-by: Marc Romeyn <marcromeyn@gmail.com>
Signed-off-by: Marc Romeyn <marcromeyn@gmail.com>
anushaknvidia
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rkalaniNV
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Apr 30, 2026
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| | [RAG Agent with Nemotron RAG Models](RAG Agent with Nemotron RAG Models/README.md) | End-to-end example of a Retrieval-Augmented Generation (RAG) agent workflow using Nemotron RAG models through Hugging Face and Nemotron 9B hosted through build.nvidia.com models | | ||
| | [Data Science ML Agent](Data Science ML Agent/README.md) | End-to-end example of a natural language-driven data science and machine learning agent powered by NVIDIA GPUs. The agent allows users to perform data exploration, model training, and hyperparameter optimization interactively using RAPIDS cuDF and cuML for GPU acceleration.| | ||
| | [Build Your Own Benchmark (BYOB)](build-your-own-benchmark/build_mcq_benchmark.ipynb) | End-to-end **Build Your Own Benchmark** flow for MMLU-style multiple-choice: prepare seed data, run a staged Data Designer pipeline (draft, judge, dedupe, distractor checks), and export a `benchmark.parquet`. See `build-your-own-benchmark/download_wikipedia_data.ipynb` to build source text from Wikipedia. | |
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Compilation fails with invalid nested f-strings.
Please add test cases for the byob pipeline.
There is no readme for the review.
Dependencies are not put in pyproject.toml and uv.lock
Please run Nemotron's pre-commit hooks
What is assets folder in the usecase README?
Please take a look at the translation branch for a checklist of agentic skills.
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