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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/)
- [Ollama](nvidia/ollama/)
- [Open WebUI with Ollama](nvidia/open-webui/)
- [Fine tune with Pytorch](nvidia/pytorch-fine-tune/)
- [RAG application in AI Workbench](nvidia/rag-ai-workbench/)
- [Fine-tune with Pytorch](nvidia/pytorch-fine-tune/)
- [RAG Application in AI Workbench](nvidia/rag-ai-workbench/)
- [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/)
- [Text to Knowledge Graph](nvidia/txt2kg/)
- [Unsloth on DGX Spark](nvidia/unsloth/)

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

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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

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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