Post-Train NVIDIA Cosmos 3 With TAO 7 Agent Skills

NVIDIA Cosmos 3 is a new open world reasoning vision-language model (VLM). NVIDIA TAO 7 is a suite of agent skills and tools for fine-tuning vision AI models like Cosmos 3 with coding agents and natural language prompts. In this tutorial, you’ll learn how to install TAO skills in Codex, customize NVIDIA Cosmos 3 reasoning VLM for any domain, and automatically optimize hyperparameters with AutoML to deliver the best accuracy for your use case. Chapter 00:00 Introduction to TAO Agent Skills 01:36 Installing & Configuring TAO Skills 02:53 LoRA Fine-Tuning 04:33 Optimizing with TAO AutoML 06:08 Final Results & Experiment Report 06:54 Conclusion Q: What is NVIDIA Cosmos 3 and what makes it unique? A: Cosmos 3 is a frontier, open-world omnimodel for physical AI that natively unifies text, image, video, audio, and actions under a single Mixture-of-Transformers architecture. Q: How can I use natural language to fine-tune a vision language model (VLM) to improve KPI? A: Install the TAO Skills, then describe your task in plain language, the agent selects the right skill, runs fine-tuning, and reports results automatically. Q: How do I make a vision language model (VLM) more accurate? A: Leverage the TAO AutoML skill to execute structured, parallel parameter sweeps. Q: What is the benefit of LoRA over full-parameter SFT for video data? A: Resource optimization. LoRA freezes base weights to prevent general knowledge regression while requiring roughly 7x fewer GPU-hours than full-parameter SFT. Resources Tech Blog: https://nvda.ws/4wkbku1 Livestream- Post-Train NVIDIA Cosmos 3 In a Day with NVIDIA TAO Agent Skills: https://www.youtube.com/watch?v=lKaqbYa0HUE Cosmos Web Page: https://nvda.ws/3RuLqV0 TAO Product Page: https://nvda.ws/4vcIr1Z TAO skills on GitHub: https://nvda.ws/4uHMcf5