mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
synced 2026-04-27 12:23:51 +00:00
a680d0472b
Adds a Claude Code plugin structure that exposes each NVIDIA DGX Spark
playbook as a triggerable skill, with an index skill ('dgx-spark') that
routes users to the right leaf based on intent and encodes the
relationship graph between playbooks (prerequisites, alternatives,
composes-with, upgrade paths).
Structure:
- overrides/*.md hand-curated frontmatter + Related sections
- scripts/generate.mjs zero-dep Node generator: nvidia + overrides → skills
- scripts/install.sh symlinks skills into ~/.claude/skills (--plugin mode available)
- skills/ committed, browsable, installable without Node
- .github/workflows/ auto-regenerates skills/ when playbooks/overrides change
Initial curated leaves: ollama, open-webui, vllm, connect-to-your-spark.
Remaining 37 leaves use generator fallback (title + tagline + summary
extracted from README) and can be curated incrementally via overrides/.
30 lines
1.9 KiB
Markdown
30 lines
1.9 KiB
Markdown
---
|
|
name: dgx-spark-nim-llm
|
|
description: Deploy a NIM on Spark — on NVIDIA DGX Spark. Use when setting up nim-llm on Spark hardware.
|
|
---
|
|
|
|
<!-- GENERATED:BEGIN from nvidia/nim-llm/README.md -->
|
|
# NIM on Spark
|
|
|
|
> Deploy a NIM on Spark
|
|
|
|
NVIDIA NIM is containerized software for fast, reliable AI model serving and inference on NVIDIA GPUs. This playbook demonstrates how to run NIM microservices for LLMs on DGX Spark devices, enabling local GPU inference through a simple Docker workflow. You'll authenticate with NVIDIA's registry, launch the NIM inference microservice, and perform basic inference testing to verify functionality.
|
|
|
|
### What you'll accomplish
|
|
|
|
You'll launch a NIM container on your DGX Spark device to expose a GPU-accelerated HTTP endpoint for text completions. While these instructions feature working with the Llama 3.1 8B NIM, additional NIM including the [Qwen3-32 NIM](https://catalog.ngc.nvidia.com/orgs/nim/teams/qwen/containers/qwen3-32b-dgx-spark) are available for DGX Spark (see them [here](https://docs.nvidia.com/nim/large-language-models/1.14.0/release-notes.html#new-language-models%20)).
|
|
|
|
### What to know before starting
|
|
|
|
**Outcome**: You'll launch a NIM container on your DGX Spark device to expose a GPU-accelerated HTTP endpoint for text completions. While these instructions feature working with the Llama 3.1 8B NIM, additional NIM including the [Qwen3-32 NIM](https://catalog.ngc.nvidia.com/orgs/nim/teams/qwen/containers/qwen3-32b-dgx-spark) are available for DGX Spark (see them [here](https://docs.nvidia.com/nim/large-language-models/1.14.0/release-notes.html#new-language-models%20)).
|
|
|
|
### What to know before starting
|
|
|
|
- Working in a terminal environment
|
|
- Using Docker commands and GPU-enabled containers
|
|
- Basic familiarity with REST APIs and curl commands
|
|
- Understanding of NVIDIA GPU environments and CUDA
|
|
|
|
**Full playbook**: `/Users/jkneen/Documents/GitHub/dgx-spark-playbooks/nvidia/nim-llm/README.md`
|
|
<!-- GENERATED:END -->
|