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1.38.12 (#8313)
Patch version increment to 1.38.12 **Base branch:** `main` --------- Co-authored-by: christian-byrne <72887196+christian-byrne@users.noreply.github.com> Co-authored-by: github-actions <github-actions@github.com> Co-authored-by: Alexander Brown <drjkl@comfy.org>
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Comfy Org PR Bot
@@ -447,43 +447,6 @@
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}
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}
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},
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"ByteDanceImageEditNode": {
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"display_name": "ByteDance Image Edit",
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"description": "Edit images using ByteDance models via api based on prompt",
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"inputs": {
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"model": {
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"name": "model"
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},
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"image": {
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"name": "image",
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"tooltip": "The base image to edit"
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},
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"prompt": {
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"name": "prompt",
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"tooltip": "Instruction to edit image"
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},
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"seed": {
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"name": "seed",
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"tooltip": "Seed to use for generation"
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},
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"guidance_scale": {
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"name": "guidance_scale",
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"tooltip": "Higher value makes the image follow the prompt more closely"
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},
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"watermark": {
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"name": "watermark",
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"tooltip": "Whether to add an \"AI generated\" watermark to the image"
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},
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"control_after_generate": {
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"name": "control after generate"
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}
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},
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"outputs": {
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"0": {
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"tooltip": null
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}
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}
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},
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"ByteDanceImageNode": {
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"display_name": "ByteDance Image",
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"description": "Generate images using ByteDance models via api based on prompt",
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@@ -6068,7 +6031,7 @@
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}
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},
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"LoraLoader": {
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"display_name": "Load LoRA",
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"display_name": "Load LoRA (Model and CLIP)",
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"description": "LoRAs are used to modify diffusion and CLIP models, altering the way in which latents are denoised such as applying styles. Multiple LoRA nodes can be linked together.",
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"inputs": {
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"model": {
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@@ -6101,8 +6064,62 @@
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}
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}
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},
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"LoraLoaderBypass": {
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"display_name": "Load LoRA (Bypass) (For debugging)",
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"description": "Apply LoRA in bypass mode. Unlike regular LoRA, this doesn't modify model weights - instead it injects the LoRA computation during forward pass. Useful for training scenarios.",
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"inputs": {
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"model": {
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"name": "model",
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"tooltip": "The diffusion model the LoRA will be applied to."
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},
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"clip": {
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"name": "clip",
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"tooltip": "The CLIP model the LoRA will be applied to."
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},
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"lora_name": {
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"name": "lora_name",
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"tooltip": "The name of the LoRA."
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},
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"strength_model": {
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"name": "strength_model",
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"tooltip": "How strongly to modify the diffusion model. This value can be negative."
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},
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"strength_clip": {
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"name": "strength_clip",
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"tooltip": "How strongly to modify the CLIP model. This value can be negative."
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}
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},
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"outputs": {
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"0": {
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"tooltip": "The modified diffusion model."
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},
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"1": {
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"tooltip": "The modified CLIP model."
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}
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}
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},
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"LoraLoaderBypassModelOnly": {
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"display_name": "Load LoRA (Bypass, Model Only) (for debugging)",
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"description": "Apply LoRA in bypass mode. Unlike regular LoRA, this doesn't modify model weights - instead it injects the LoRA computation during forward pass. Useful for training scenarios.",
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"inputs": {
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"model": {
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"name": "model"
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},
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"lora_name": {
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"name": "lora_name"
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},
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"strength_model": {
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"name": "strength_model"
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}
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},
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"outputs": {
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"0": {
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"tooltip": "The modified diffusion model."
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}
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}
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},
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"LoraLoaderModelOnly": {
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"display_name": "LoraLoaderModelOnly",
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"display_name": "Load LoRA",
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"description": "LoRAs are used to modify diffusion and CLIP models, altering the way in which latents are denoised such as applying styles. Multiple LoRA nodes can be linked together.",
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"inputs": {
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"model": {
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@@ -6834,6 +6851,126 @@
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}
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}
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},
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"MagnificImageRelightNode": {
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"display_name": "Magnific Image Relight",
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"description": "Relight an image with lighting adjustments and optional reference-based light transfer.",
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"inputs": {
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"image": {
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"name": "image",
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"tooltip": "The image to relight."
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},
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"prompt": {
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"name": "prompt",
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"tooltip": "Descriptive guidance for lighting. Supports emphasis notation (1-1.4)."
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},
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"light_transfer_strength": {
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"name": "light_transfer_strength",
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"tooltip": "Intensity of light transfer application."
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},
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"style": {
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"name": "style",
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"tooltip": "Stylistic output preference."
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},
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"interpolate_from_original": {
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"name": "interpolate_from_original",
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"tooltip": "Restricts generation freedom to match original more closely."
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},
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"change_background": {
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"name": "change_background",
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"tooltip": "Modifies background based on prompt/reference."
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},
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"preserve_details": {
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"name": "preserve_details",
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"tooltip": "Maintains texture and fine details from original."
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},
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"advanced_settings": {
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"name": "advanced_settings",
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"tooltip": "Fine-tuning options for advanced lighting control."
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},
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"reference_image": {
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"name": "reference_image",
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"tooltip": "Optional reference image to transfer lighting from."
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}
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},
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"outputs": {
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"0": {
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"tooltip": null
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}
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}
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},
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"MagnificImageSkinEnhancerNode": {
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"display_name": "Magnific Image Skin Enhancer",
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"description": "Skin enhancement for portraits with multiple processing modes.",
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"inputs": {
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"image": {
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"name": "image",
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"tooltip": "The portrait image to enhance."
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},
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"sharpen": {
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"name": "sharpen",
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"tooltip": "Sharpening intensity level."
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},
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"smart_grain": {
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"name": "smart_grain",
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"tooltip": "Smart grain intensity level."
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},
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"mode": {
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"name": "mode",
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"tooltip": "Processing mode: creative for artistic enhancement, faithful for preserving original appearance, flexible for targeted optimization."
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}
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},
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"outputs": {
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"0": {
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"tooltip": null
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}
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}
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},
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"MagnificImageStyleTransferNode": {
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"display_name": "Magnific Image Style Transfer",
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"description": "Transfer the style from a reference image to your input image.",
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"inputs": {
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"image": {
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"name": "image",
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"tooltip": "The image to apply style transfer to."
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},
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"reference_image": {
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"name": "reference_image",
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"tooltip": "The reference image to extract style from."
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},
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"prompt": {
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"name": "prompt"
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},
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"style_strength": {
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"name": "style_strength",
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"tooltip": "Percentage of style strength."
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},
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"structure_strength": {
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"name": "structure_strength",
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"tooltip": "Maintains the structure of the original image."
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},
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"flavor": {
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"name": "flavor",
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"tooltip": "Style transfer flavor."
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},
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"engine": {
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"name": "engine",
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"tooltip": "Processing engine selection."
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},
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"portrait_mode": {
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"name": "portrait_mode",
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"tooltip": "Enable portrait mode for facial enhancements."
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},
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"fixed_generation": {
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"name": "fixed_generation",
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"tooltip": "When disabled, expect each generation to introduce a degree of randomness, leading to more diverse outcomes."
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}
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},
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"outputs": {
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"0": {
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"tooltip": null
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}
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}
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},
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"Mahiro": {
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"display_name": "Mahiro CFG",
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"description": "Modify the guidance to scale more on the 'direction' of the positive prompt rather than the difference between the negative prompt.",
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@@ -13918,24 +14055,24 @@
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"name": "bucket_mode",
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"tooltip": "Enable resolution bucket mode. When enabled, expects pre-bucketed latents from ResolutionBucket node."
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},
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"bypass_mode": {
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"name": "bypass_mode",
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"tooltip": "Enable bypass mode for training. When enabled, adapters are applied via forward hooks instead of weight modification. Useful for quantized models where weights cannot be directly modified."
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},
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"control_after_generate": {
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"name": "control after generate"
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}
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},
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"outputs": {
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"0": {
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"name": "model",
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"tooltip": "Model with LoRA applied"
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},
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"1": {
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"name": "lora",
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"tooltip": "LoRA weights"
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},
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"2": {
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"1": {
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"name": "loss_map",
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"tooltip": "Loss history"
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},
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"3": {
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"2": {
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"name": "steps",
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"tooltip": "Total training steps"
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}
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