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README.md

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* [What's New?](#whats-new)
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* [Data Flywheel](#data-flywheel)
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* [NeMo Data Designer](#nemo-data-designer)
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* [Safer Agentic AI](#safer-agentic-ai)
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* [Knowledge Graph RAG](#knowledge-graph-rag)
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* [Agentic Workflows with Llama 3.1](#agentic-workflows-with-llama-31)
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- [Tool Calling Fine-tuning, Inference, Evaluation, and Guardrailing with NVIDIA NeMo Microservices and NIMs](./nemo/data-flywheel/tool-calling)
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- [Embedding Fine-tuning, Inference, and Evaluation with NVIDIA NeMo Microservices and NIMs](./nemo/data-flywheel/embedding-finetuning/)
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### NeMo Data Designer
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NeMo Data Designer is purpose-built for AI developers to design high-quality, domain-specific synthetic data at scale—unlike one-size-fits-all LLMs that struggle to deliver consistent, reliable results. Start from scratch or just a few seed examples to accelerate AI development, saving time while improving model performance and accuracy.
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Check out some of these tutorials to get started!
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- [The Basics: Generate Product Review Datasets](./nemo/NeMo-Data-Designer/intro-tutorials/1-the-basics.ipynb)
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- [Structured Outputs and Jinja Expressions](./nemo/NeMo-Data-Designer/intro-tutorials/2-structured-outputs-and-jinja-expressions.ipynb)
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- [Seeding with External Datasets](./nemo/NeMo-Data-Designer/intro-tutorials/3-seeding-with-a-dataset.ipynb)
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Once you're done with the basics, check out some Data Designer use cases [here](./nemo/NeMo-Data-Designer/community-contributions).
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### Safer Agentic AI
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The following tutorials illustrate how to audit your large language models with NeMo Auditor to identify vulnerabilities to unsafe prompts, and how to run inference with multiple rails in parallel to reduce latency and improve throughput.

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