NVIDIA's TAO 7 Lets Claude Code Train Vision AI in Plain English

NVIDIA TAO 7 is now generally available, and it represents a fundamental rethink of how you interact with a model training toolkit. Instead of editing YAML configs or memorizing CLI flags, you describe what you want in plain English to your coding agent, and TAO handles the rest. The toolkit ships as a plugin for Claude Code and Codex, exposing every training workflow as a structured skill contract the agent reads to plan and dispatch jobs.

From CLI to conversation

TAO 7 adds a suite of agent skills and tools for fine-tuning vision AI models with coding agents and natural language prompts. The core idea is that the entire toolkit, including model training, data prep, hyperparameter search, and deployment, is now surfaced as a skill bank that any compatible coding agent can consume. You install the plugin, and from that point on your agent knows how to run every TAO workflow.

The skill bank works with Codex, Claude Code, and NemoClaw. It is a plugin published to coding-agent marketplaces that exposes every model, data transform, platform backend, and application workflow as a SKILL.md contract the agent reads to plan jobs. Crucially, most skills require zero Python: the agent constructs docker run commands directly, so the only hard dependencies are Docker and an NVIDIA GPU.

Four things that are actually new

• Agent skills: Fine-tune open models, including Cosmos 3, using natural language with any coding agent. The skill bank bundles 56 skills across model training, data preparation, platform backends, and end-to-end application workflows.
• LLM-guided AutoML: Automated hyperparameter optimization using the AutoML agent achieves the highest accuracy and converges quickly with LLM-generated reasoning. This converges 2x faster toward accuracy targets. Six new search algorithms are included: BOHB, BFBO, ASHA, PBT, DEHB, and Hyperband-ES, with Weights & Biases integration.