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Delete workflows/qwen-loras-very-good-nsfw-v2.json

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  1. workflows/qwen-loras-very-good-nsfw-v2.json +0 -1517
workflows/qwen-loras-very-good-nsfw-v2.json DELETED
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- "## Qwen Image Edit - Master Workflow (v2: resolution control)\n\n### WHERE THE OUTPUT SIZE COMES FROM\nThe output image size == the latent fed to **KSampler** (`latent_image`).\nThat latent is `VAEEncode( primary image )`. So:\n\n**OUTPUT W x H = the `OUTPUT RESOLUTION` node (id 5) W x H.**\n\nSet width & height there (was auto ~1MP `FluxKontextImageScale`, now an explicit\n`ImageScale` you control). What you type is exactly what you get out.\n\n- Keep both W and H **divisible by 16** (VAE /8 x patch /2). 1MP = trained sweet spot.\n- Want to LOCK aspect ratio? set ONE of W/H to **0** -> the other is computed from\n the source aspect (core ImageScale behaviour). e.g. W=0, H=1152.\n- `crop=disabled` = fit exactly (may stretch if aspect differs); `center` = crop-to-fill.\n- Qwen-Edit is trained ~1 megapixel. 0.8-1.3MP is the safe band; >1.5MP degrades.\n Good ~1MP buckets: 1024x1024, 1152x896, 896x1152, 1216x832, 832x1216, 1344x768.\n\n### WHAT THE MODEL ACTUALLY RECEIVES (fixed internally, from node source)\nInside each **TextEncodeQwenImageEditPlus** every input image is rescaled twice,\nno matter what you feed it:\n- **VL / understanding stream:** scaled to **384x384 area** (~0.15MP) for Qwen2.5-VL.\n- **Reference latent (pixel copy):** scaled to **~1024x1024 area, rounded to /8**, VAE-encoded.\nSo reference/second images do NOT need to be high-res, and the `REF RESOLUTION`\nnode only affects what gets handed in before that internal rescale.\n\n### SPEED vs QUALITY (unchanged)\nFlip the **Accelerate?** boolean (bottom-left) - drives MODEL / STEPS / CFG switches:\n- ON = Lightning 4-step LoRA, 4 steps, CFG 1.0 (fast)\n- OFF = no Lightning, 20 steps, CFG 4.0 (best quality)\n\nContent LoRAs -> **Power Lora Loader** (applied in both modes).\nUNET: `qwen_image_edit_2511_*`. Bigger output = more VRAM + slower, quadratically."
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