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chore: Regenerate all playbooks

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README.md
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@ -37,10 +37,10 @@ Each playbook includes prerequisites, step-by-step instructions, troubleshooting
- [NVFP4 Quantization](nvidia/nvfp4-quantization/) - [NVFP4 Quantization](nvidia/nvfp4-quantization/)
- [Ollama](nvidia/ollama/) - [Ollama](nvidia/ollama/)
- [Open WebUI with Ollama](nvidia/open-webui/) - [Open WebUI with Ollama](nvidia/open-webui/)
- [Fine tune with Pytorch](nvidia/pytorch-fine-tune/) - [Fine-tune with Pytorch](nvidia/pytorch-fine-tune/)
- [RAG application in AI Workbench](nvidia/rag-ai-workbench/) - [RAG Application in AI Workbench](nvidia/rag-ai-workbench/)
- [Speculative Decoding](nvidia/speculative-decoding/) - [Speculative Decoding](nvidia/speculative-decoding/)
- [Set up Tailscale on your Spark](nvidia/tailscale/) - [Set up Tailscale on Your Spark](nvidia/tailscale/)
- [TRT LLM for Inference](nvidia/trt-llm/) - [TRT LLM for Inference](nvidia/trt-llm/)
- [Text to Knowledge Graph](nvidia/txt2kg/) - [Text to Knowledge Graph](nvidia/txt2kg/)
- [Unsloth on DGX Spark](nvidia/unsloth/) - [Unsloth on DGX Spark](nvidia/unsloth/)

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nvidia/jax/README.md
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# Optimized JAX # Optimized JAX
> Optimize JAX to Run on Spark > Optimize JAX to run on Spark
## Table of Contents ## Table of Contents

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nvidia/pytorch-fine-tune/README.md
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# Fine tune with Pytorch # Fine-tune with Pytorch
> Use Pytorch to fine-tune models locally > Use Pytorch to fine-tune models locally

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nvidia/rag-ai-workbench/README.md
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# RAG application in AI Workbench # RAG Application in AI Workbench
> Install and use AI Workbench to clone and run a reproducible RAG application > Install and use AI Workbench to clone and run a reproducible RAG application

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nvidia/tailscale/README.md
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# Set up Tailscale on your Spark # Set up Tailscale on Your Spark
> Use Tailscale to connect to your Spark on your home network no matter where you are > Use Tailscale to connect to your Spark on your home network no matter where you are