Upload help_mixmod_v1 Annotated_v2.json

help_mixmod_v1 Annotated_v2.json

@@ -0,0 +1,1739 @@
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+        "masterpiece, best quality, digital media \\(artwork\\),\n(furry, anthro,) 4 toes, full body, digitigrade,\nfront view, gradient background, multicolored background,\nfox, female, slim, cute, medium breasts, blue eyes, long hair, wavey hair, brown hair,  happy, joyful, \nwhite tank top, green skirt,\nstanding, facing viewer, smile, v sign, hand on own hip, crossed legs, looking at viewer,"
+      ],
+      "color": "#232",
+      "bgcolor": "#353"
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+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 44
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            2
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+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
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+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "masterpiece, best quality, digital media \\(artwork\\),\n(furry, anthro,) 4 toes, full body, digitigrade,\nfront view, gradient background, multicolored background,\nfox, female, slim, cute, medium breasts, blue eyes, long hair, wavey hair, brown hair,  happy, joyful, \nwhite tank top, green skirt,\nstanding, facing viewer, smile, v sign, hand on own hip, crossed legs, looking at viewer,"
+      ],
+      "color": "#232",
+      "bgcolor": "#353"
+    },
+    {
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+      "type": "Note",
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+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "ComfyUI doesn't autodetect VPred/ZSNR for GGUFs, so this is needed for that."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 5,
+      "type": "MixModGuiderComponentPipelineNode",
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+          "type": "COMPONENT",
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+        },
+        {
+          "name": "options",
+          "shape": 7,
+          "type": "OPTIONS",
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+      ],
+      "outputs": [
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+          "type": "COMPONENT",
+          "links": [
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+      ],
+      "properties": {
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+        "ver": "e2f298e4cb6460d77de61033065e82fdd53bb9e2",
+        "Node name for S&R": "MixModGuiderComponentPipelineNode"
+      },
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+    },
+    {
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+      "flags": {},
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+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Generally you'll want the ratio between 0.4-0.6 for the modes that it actually works on (Barring FFT_Overlap), but do as you please. Higher ratios favor the second model, lower the first"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 27,
+      "type": "MixModFFTGuiderNode",
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+      "inputs": [
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+      ],
+      "outputs": [
+        {
+          "name": "GUIDER",
+          "type": "GUIDER",
+          "links": null
+        }
+      ],
+      "properties": {
+        "aux_id": "kantsche/ComfyUI-MixMod",
+        "ver": "e2f298e4cb6460d77de61033065e82fdd53bb9e2",
+        "Node name for S&R": "MixModFFTGuiderNode"
+      },
+      "widgets_values": [
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+        1
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+    },
+    {
+      "id": 29,
+      "type": "Note",
+      "pos": [
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+      "size": [
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+      ],
+      "flags": {},
+      "order": 13,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "First model in the chain does matter, as most Mixmod Guider functions use the first model as the leader for various functions. Generally the first in leads the anatomy as well."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 40,
+      "type": "Note",
+      "pos": [
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+      "size": [
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+      "flags": {},
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+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Prompts should be equal, or closely matched for dissimilar models.\n\nDissimilar meaning the differences between Noob/Illustrious, Pony, Juggernaut, SeaArt, Base SDXL, or any other finetunes that have been trained by different teams on different datasets.\n\nAsking one model to generate a fox and the other to generate a horse will likely turn your gen into a modern piccasso impression as they fight between each other."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 33,
+      "type": "Note",
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+      "order": 15,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Base_Weight works with any of the non-FFT/Band guiders, though it is a bit weak in its influence. Standard guiders iterate faster than any of the FFT/Band guiders, so if you're really struggling with generation times you can experiment with the weights instead."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
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+      "type": "Note",
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+        "Schedules the model to influence the gen or not. Be aware that some FFT Guider modes will just create a black square if you schedule the first model in. Modes affected are: 2M2F, TeamFFT4Freq, FFT_Overlap, FFT_Full\n\nThis can be used to help pull composition/anatomy from the first loaded model, then halt it to both let the second model take the lead and restore your it/s back to regular gen speed."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
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+      "type": "Note",
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+      "flags": {},
+      "order": 17,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Had weird noise issues when using the first model as the scheduler guider, so we connect the second instead. Might be a VPred/ZSNR problem. Mixmod works when mixing different prediction models together however."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
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+      "type": "Note",
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+        "GGUFs will gen slower than checkpoints due to the compression. If you have ~16GB of VRAM, you can use the checkpoint versions together, but your gen speed will still be halved compared to 1 model as it's generating 2 predictions for the 2 models, then averaging them together.\n\nIf you're really struggling with VRAM, you can split checkpoints into their Unet+CLIPs with the Modelsave and CLIPsave nodes, then set the CLIP loader's device to CPU, which will make your CPU generate the conditioning tokens. It's still pretty fast, to the point where even new models like Z-image and Newbie recommend you offload the CLIPs to CPU so your VRAM is fully available for the unets/DiTs."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 30,
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+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "properties": {},
+      "widgets_values": [
+        "Second in Model is generally for style, though some FFT Guider modes can change the balance"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
+      "id": 41,
+      "type": "Note",
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+      "widgets_values": [
+        "The standard Mixmod Guider node favors the first model in. You can schedule the models or change to the FFT Guider and its modes to balance this. Base_Weight will work with non-FFT/Band nodes, though it's influence is a bit weak"
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
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+      "type": "Note",
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+      "widgets_values": [
+        "Unmentioned guider nodes are either not fully implemented, and thus fallback to the standard guider, or have setup conditions that I have yet to understand or just plain throw an error on attempting to use them. Affected nodes are: High Res (unimplemented), Depth (broken on SDXL), and Dynamic Mask Alternative (broken).\n\nBand_FFT is coded but has outputs that are just a softer variation seed of Standard/TeamFFT. FFT_Full is pretty much the same thing, so you can use that instead of connecting the node in."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
+    },
+    {
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+        "FFT modes aren't well documented, but what I've found is:\n\nTeamFFT: Similar to the standard guider. Ratio doesn't work but I guess this simplifies your setup if you want to use the FFT Node in your workflow.\n\n2model_FFT: Similar to 2M2F in theory, but does not have a hard cutoff for the frequency selection, thus can be considered a lighter 2M2F. You may need to push the slider harder than 2M2F to get similar outputs, like starting at 0.75 if you want more of the second model to show through. Still not as strong as 2M2F even at 0.9+ ratios, but much less likely to have body horror with dissimilar models. Still a worthy mode and one I use often.\n\n2M2F: Your bread and butter if you're using styles from dissimilar models, such as trying to combine Noob and [Pony/Juggernaut/Auraflow/SeaArt] together. Splits the models attention between high/low frequency noise, with 'how much' each model deals with being handled by the slider. Second model in handles the texturing here. Much higher chance than the other modes to break into a piccasso artwork with dissimilar models, but much more accurate to the second model. This one wants a light touch for ratios, between 0.4 and 0.6 depending if you want to favor the first model or the second.\n\nTeamFFT4Freq: Similar to TeamFFT except the models attention is split between 4 frequencies. Creates internal masks for the bands to try and focus each model's attention. In practice, it's just another TeamFFT that also doesn't work with the ratio slider. It might be for 3+ model setups but that's just getting excessive.\n\nFFT_Overlap: 2M2F-like with outputs favoring using the second model for texture, ratio controls how far models are allowed to overlap. Here you will get some milage out of having the ratio from 0.2-0.35, as going above those values tends to turn it into another standard guider. I have experienced overexposure problems during inpainting however, so this is a bit of a YMMV mode.\n\nFFT_Full: Another standard guider mode, though it does seem to favor the second model a bit more. Ratio doesn't work.\n"
+      ],
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+        "Be aware that you can only mixmod with models that share the same latent space, and thus the same VAE. Trying to load, say, FLUX and SDXL will just throw an error at you saying the latent dimensions don't match. There is a LORA that downconverts SDXL models to use SD1 latent space however, if you want to mixmod with SDXL and SD1.5. That one is under ostris' huggingface as sdxl-sd1-vae-lora. It's not perfect but it does work."
+      ],
+      "color": "#432",
+      "bgcolor": "#653"
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+        "December12th2025 update: I was wrong about the Dynamic Mask Guider. Its job is to mask areas using model attention to create areas for each model to work on, with a per-step decay on how strong Model#1's masks are. In practice, this is a 2model_FFT-like guide function that schedules the model's influence while being effected by base_weight values and not dying if you schedule models. It also iterates faster than FFT modes.\n\nIn my experience:\nDecay_Factor: Probably the most important part. Influences how fast/how strong the first model falls over into the second, with low values like 0.1 still allowing model#1 to influence the gen to the end step and high values like 0.9+ letting model#2 take the lead to the point where model#1 hardly shows up in the final gen. You can combine this with scheduling the first model to stop 33-50% of the way through to have practically no influence at all in the final output. \n\nThreshold: The name is a bit misleading, as I've found it influences how strong model#2 is in the starting steps of the generation, with low values like 0.1 being weak and the maximum value of 0.5 being strong. In some cases this will do nothing at all, and in others it'll let model#2 guide the composition just as strongly as model#1, which may be unwanted if model#2 has composition/anatomy issues.\n\nBlur_Sigma: I believe this is supposed to blur the edges of the attention masks of the models, similar to how blurring masks for inpainting works. In practice, kind of works like a weird seed variation. There's no harm in keeping this one at the default values 99.9% of the time."
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