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Collection of step-by-step playbooks for setting up AI/ML workloads on NVIDIA DGX Spark devices with Blackwell architecture.
Updated the README to remove cleanup instructions and clarify next steps. Do not remove IPs that we set up in separate guide within this playbook |
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DGX Spark Playbooks
Collection of step-by-step playbooks for setting up AI/ML workloads on NVIDIA DGX Spark devices with Blackwell architecture.
About
These playbooks provide detailed instructions for:
- Installing and configuring popular AI frameworks
- Running inference with optimized models
- Setting up development environments
- Connecting and managing your DGX Spark device
Each playbook includes prerequisites, step-by-step instructions, troubleshooting guidance, and example code.
Available Playbooks
NVIDIA
- Comfy UI
- Set Up Local Network Access
- Connect Two Sparks
- CUDA-X Data Science
- DGX Dashboard
- FLUX.1 Dreambooth LoRA Fine-tuning
- Optimized JAX
- LLaMA Factory
- Build and Deploy a Multi-Agent Chatbot
- Multi-modal Inference
- NCCL for Two Sparks
- Fine-tune with NeMo
- NIM on Spark
- NVFP4 Quantization
- Ollama
- Open WebUI with Ollama
- Fine-tune with Pytorch
- RAG Application in AI Workbench
- SGLang Inference Server
- Speculative Decoding
- Set up Tailscale on Your Spark
- TRT LLM for Inference
- Text to Knowledge Graph
- Unsloth on DGX Spark
- Vibe Coding in VS Code
- Install and Use vLLM for Inference
- VS Code
- Build a Video Search and Summarization (VSS) Agent
Resources
- Documentation: https://www.nvidia.com/en-us/products/workstations/dgx-spark/
- Developer Forum: https://forums.developer.nvidia.com/c/accelerated-computing/dgx-spark-gb10
- Terms of Service: https://assets.ngc.nvidia.com/products/api-catalog/legal/NVIDIA%20API%20Trial%20Terms%20of%20Service.pdf
License
See:
- LICENSE for licensing information.
- LICENSE-3rd-party for third-party licensing information.
