NVIDIA/dgx-spark-playbooks
Collection of configuration playbooks for deploying AI/ML frameworks, fine-tuning models, and running inference on NVIDIA DGX Spark devices.
Collecting fresh signals — velocity needs a few days of history.
collecting data…
star history
This repository provides detailed step-by-step guides for configuring AI frameworks on NVIDIA DGX Spark Blackwell architecture hardware. It includes playbooks for popular tools such as llama.cpp, LLaMA Factory, LM Studio, NeMo fine-tuning, NIM LLM serving, and multi-agent systems. Each playbook covers prerequisites, installation steps, and troubleshooting for developers setting up AI development environments.
Frequently asked
- What is NVIDIA/dgx-spark-playbooks?
- Collection of configuration playbooks for deploying AI/ML frameworks, fine-tuning models, and running inference on NVIDIA DGX Spark devices.
- Is dgx-spark-playbooks open source?
- Yes — NVIDIA/dgx-spark-playbooks is open source, released under the Apache-2.0 license.
- What language is dgx-spark-playbooks written in?
- NVIDIA/dgx-spark-playbooks is primarily written in Jupyter Notebook.
- How popular is dgx-spark-playbooks?
- NVIDIA/dgx-spark-playbooks has 1k stars on GitHub.
- Where can I find dgx-spark-playbooks?
- NVIDIA/dgx-spark-playbooks is on GitHub at https://github.com/NVIDIA/dgx-spark-playbooks.