mirror of
https://github.com/NVIDIA/dgx-spark-playbooks.git
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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/.
29 lines
1.9 KiB
Markdown
29 lines
1.9 KiB
Markdown
---
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name: dgx-spark-flux-finetuning
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description: Fine-tune FLUX.1-dev 12B model using Dreambooth LoRA for custom image generation — on NVIDIA DGX Spark. Use when setting up flux-finetuning on Spark hardware.
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---
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<!-- GENERATED:BEGIN from nvidia/flux-finetuning/README.md -->
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# FLUX.1 Dreambooth LoRA Fine-tuning
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> Fine-tune FLUX.1-dev 12B model using Dreambooth LoRA for custom image generation
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This playbook demonstrates how to fine-tune the FLUX.1-dev 12B model using multi-concept Dreambooth LoRA (Low-Rank Adaptation) for custom image generation on DGX Spark.
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With 128GB of unified memory and powerful GPU acceleration, DGX Spark provides an ideal environment for training an image generation model with multiple models loaded in memory, such as the Diffusion Transformer, CLIP Text Encoder, T5 Text Encoder, and the Autoencoder.
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Multi-concept Dreambooth LoRA fine-tuning allows you to teach FLUX.1 new concepts, characters, and styles. The trained LoRA weights can be easily integrated into existing ComfyUI workflows, making it perfect for prototyping and experimentation.
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Moreover, this playbook demonstrates how DGX Spark can not only load several models in memory, but also train and generate high-resolution images such as 1024px and higher.
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**Outcome**: You will have a fine-tuned FLUX.1 model capable of generating images with your custom concepts, readily available for ComfyUI workflows.
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The setup includes:
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- FLUX.1-dev model fine-tuning using Dreambooth LoRA technique
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- Training on custom concepts ("tjtoy" toy and "sparkgpu" GPU)
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- High-resolution 1K diffusion training and inference
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- ComfyUI integration for intuitive visual workflows
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- Docker containerization for reproducible environments
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Duration: * 30-45 minutes for initial setup model download time
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**Full playbook**: `/Users/jkneen/Documents/GitHub/dgx-spark-playbooks/nvidia/flux-finetuning/README.md`
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<!-- GENERATED:END -->
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