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marcromeyn merged 1 commit into from
Dec 18, 2025
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Adding video to README.md #42

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33 changes: 29 additions & 4 deletions README.md
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# NVIDIA Nemotron Developer Repository

Developer companion repo for working with NVIDIA's Nemotron models: inference, fine-tuning, agents, visual reasoning, deployment, and complete training recipes.
**Open and efficient models for agentic AI** — training recipes, deployment guides, and use-case examples for the Nemotron family.

[![Python 3.10+](https://img.shields.io/badge/python-3.10%2B-blue.svg)](https://www.python.org/downloads/)
[![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0)
[![Contributions Welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg)](CONTRIBUTING.md)
[![Docs](https://img.shields.io/badge/docs-dev-76B900.svg)](https://nvidia-nemo.github.io/Nemotron/dev/)

<div align="center">

[![Watch the Nemotron Overview](https://img.youtube.com/vi/_y9SEtn1lU8/maxresdefault.jpg)](https://www.youtube.com/watch?v=_y9SEtn1lU8)

**[Watch: Nemotron Overview](https://www.youtube.com/watch?v=_y9SEtn1lU8)**

</div>

---

## Why Nemotron?

| | |
|---|---|
| **Open Models** | Fully transparent training data, techniques, and weights for community innovation |
| **Compute Efficiency** | Model pruning and optimization enabling higher throughput via TensorRT-LLM |
| **High Accuracy** | Built on frontier open models with human-aligned reasoning for agentic workflows |
| **Flexible Deployment** | Deploy anywhere — edge, single GPU, or data center with NIM microservices |

---

## Repository Overview
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## What is Nemotron?

[NVIDIA Nemotron](https://developer.nvidia.com/nemotron) is a family of open, high-efficiency models with fully transparent training data, weights, and recipes.
[NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) is a family of open, high-efficiency multimodal models purpose-built for agentic AI.

**Model Tiers:**

- **Nano** — Optimized for edge and PC deployments
- **Super** — Single GPU deployment with highest throughput
- **Ultra** — Multi-GPU datacenter applications

Nemotron models are designed for **agentic AI workflows**—they excel at coding, math, scientific reasoning, tool calling, instruction following, and visual reasoning. Models are optimized for deployment across edge, single GPU, and data center environments, with support for NeMo, TensorRT-LLM, vLLM, SGLang, and NIM microservices.
Nemotron models excel at coding, math, scientific reasoning, tool calling, instruction following, and visual reasoning. Deploy across edge, single GPU, or data center environments with support for NeMo, TensorRT-LLM, vLLM, SGLang, and NIM microservices.

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**NVIDIA Nemotron** — Open, transparent, and reproducible.
**NVIDIA Nemotron** — Open and efficient models for agentic AI.
15 changes: 14 additions & 1 deletion docs/index.md
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# Nemotron Training Recipes

Reproducible training recipes for the NVIDIA Nemotron model family — transparent pipelines for data preparation, training, and evaluation across all stages.
**Open and efficient models for agentic AI** — reproducible training pipelines with fully transparent data, techniques, and weights.

<div style="text-align: center; margin: 2rem 0;">
<iframe width="560" height="315" src="https://www.youtube.com/embed/_y9SEtn1lU8" title="Nemotron Overview" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
</div>

## Quick Start

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| 1 | [SFT](train/nano3/sft.md) | Supervised fine-tuning for instruction following |
| 2 | [RL](train/nano3/rl.md) | Reinforcement learning for alignment |

## Why Nemotron?

| | |
|---|---|
| **Open Models** | Transparent training data, techniques, and weights for community innovation |
| **Compute Efficiency** | Model pruning enabling higher throughput via TensorRT-LLM |
| **High Accuracy** | Built on frontier open models with human-aligned reasoning |
| **Flexible Deployment** | Deploy anywhere — edge, single GPU, or data center with NIM |

## Key Features

- **Complete Pipelines** — From raw data to deployment-ready models
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