Editing Diffusion Models (section)

== <span style="color: #FFFFFF;">Creating</span> ==
Designing a diffusion-based image generation system:

'''1. Choose the right base model'''
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Use case assessment:
├── General creative images → SDXL 1.0 or Flux.1
├── Photorealistic portraits → Realistic Vision, Deliberate
├── Anime/illustration style → Anything-v5, DreamShaper
├── Product/e-commerce → Fine-tune on product images
└── Video generation → AnimateDiff, Sora, Stable Video Diffusion
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'''2. Customization pipeline (DreamBooth/LoRA)'''
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3-30 reference images (subject or style)
    ↓
[DreamBooth fine-tune: ~1000-2000 steps with rare token identifier]
    OR
[LoRA training: lightweight adapter, 500 MB vs 4 GB full model]
    ↓
[Inference: base model + LoRA adapter merged at generation time]
    ↓
Consistent identity/style preservation in generations
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'''3. Production inference stack'''
* Use xFormers or Flash Attention for memory-efficient attention
* Enable torch.compile() for 20-40% throughput improvement
* Batch requests across users to maximize GPU utilization
* Use model distillation (SDXL-Turbo, LCM-LoRA) for real-time applications
* Serve multiple LoRA adapters on one base model via dynamic loading

'''4. Safety layer'''
* Safety checker on outputs (NSFW classifier)
* Prompt filtering for prohibited content
* Watermarking generated images for provenance tracking

[[Category:Artificial Intelligence]]
[[Category:Generative AI]]
[[Category:Deep Learning]]
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