Retrieve repo-cited facts about Nemotron 3 Nano architecture and training.
npx skills add https://github.com/NVIDIA-NeMo/Nemotron --skill nemotron-nano3
Please help me install this Agent Skill. Skill: nemotron-nano3 Source: https://github.com/NVIDIA-NeMo/Nemotron/tree/main/skills/nemotron-nano3 Command: npx skills add https://github.com/NVIDIA-NeMo/Nemotron --skill nemotron-nano3
Nemotron 3 Nano users need fast, authoritative answers about the model’s architecture, training data, recipes, evaluation results, quantization, and deployment behavior without wading through a large repository.
Use the nemotron-nano3 skill when you ask, in plain English, for facts about how Nemotron 3 Nano works (for example: “How many experts are activated per token, and what is the active-parameter count?”).
High-intent search queries and answers about installing and using this skill.
Nemotron 3 Nano is a language model with a specific architecture and active-parameter count per token. Its design details, including activated experts, are grounded in cited chunks from the official Nano3 technical report.
Nemotron 3 Nano training involved supervised fine-tuning (SFT) and reinforcement learning methods like RLVR, GRPO, and RLHF. Authoritative facts about these pretraining and alignment recipes are retrieved directly from the model card and paper.
Released Nemotron 3 Nano checkpoints include Base, BF16, and FP8 variants. The FP8 checkpoint supports specific quantization deployment behaviors, with context and reasoning controls detailed in the official model card.
Evaluation benchmarks and throughput claims for Nemotron 3 Nano are documented in the tech report. The skill retrieves these specific performance metrics with citation-by-file-path grounding from the paper chunks.
The public Nemotron 3 Nano repo recipes expose the paper's general shape but do not reproduce proprietary training mixtures. The skill explicitly separates paper claims from these public recipe reproduction limits.
To build, fine-tune, or reproduce Nemotron 3 Nano pipelines on custom hardware, you are directed to the nemotron-customize skill. This skill handles factual questions, routing procedural build procedures to that dedicated tool.
Lhhiep-maxcodeAnswers factual questions about Nemotron 3 Nano architecture, training, evaluation, and deployment from authoritative sources.
rocklambrosAnalyze paired before/after fine-tune evaluations with McNemar, t-tests, and effect sizes.
Lhhiep-maxcodeRetrieve NVIDIA Nemotron 3 Ultra architecture, training, evaluation, and release details from source files.
NVIDIA-NeMoRetrieve cited facts about NVIDIA Nemotron 3 Super architecture and training pipeline from indexed references.
