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https://github.com/invoke-ai/InvokeAI
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feat(ui): update qr code cnet starter model
- For SD1.5, use the new V2 version - Add the SDXL version
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@ -187,164 +187,171 @@ STARTER_MODELS: list[StarterModel] = [
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# endregion
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# region ControlNet
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StarterModel(
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name="QRCode Monster",
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name="QRCode Monster v2 (SD1.5)",
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base=BaseModelType.StableDiffusion1,
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source="monster-labs/control_v1p_sd15_qrcode_monster",
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description="Controlnet model that generates scannable creative QR codes",
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source="monster-labs/control_v1p_sd15_qrcode_monster::v2",
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description="ControlNet model that generates scannable creative QR codes",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="QRCode Monster (SDXL)",
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base=BaseModelType.StableDiffusionXL,
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source="monster-labs/control_v1p_sdxl_qrcode_monster",
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description="ControlNet model that generates scannable creative QR codes",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="canny",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_canny",
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description="Controlnet weights trained on sd-1.5 with canny conditioning.",
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description="ControlNet weights trained on sd-1.5 with canny conditioning.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="inpaint",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_inpaint",
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description="Controlnet weights trained on sd-1.5 with canny conditioning, inpaint version",
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description="ControlNet weights trained on sd-1.5 with canny conditioning, inpaint version",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="mlsd",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_mlsd",
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description="Controlnet weights trained on sd-1.5 with canny conditioning, MLSD version",
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description="ControlNet weights trained on sd-1.5 with canny conditioning, MLSD version",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="depth",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11f1p_sd15_depth",
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description="Controlnet weights trained on sd-1.5 with depth conditioning",
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description="ControlNet weights trained on sd-1.5 with depth conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="normal_bae",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_normalbae",
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description="Controlnet weights trained on sd-1.5 with normalbae image conditioning",
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description="ControlNet weights trained on sd-1.5 with normalbae image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="seg",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_seg",
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description="Controlnet weights trained on sd-1.5 with seg image conditioning",
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description="ControlNet weights trained on sd-1.5 with seg image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="lineart",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_lineart",
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description="Controlnet weights trained on sd-1.5 with lineart image conditioning",
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description="ControlNet weights trained on sd-1.5 with lineart image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="lineart_anime",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15s2_lineart_anime",
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description="Controlnet weights trained on sd-1.5 with anime image conditioning",
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description="ControlNet weights trained on sd-1.5 with anime image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="openpose",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_openpose",
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description="Controlnet weights trained on sd-1.5 with openpose image conditioning",
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description="ControlNet weights trained on sd-1.5 with openpose image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="scribble",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_scribble",
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description="Controlnet weights trained on sd-1.5 with scribble image conditioning",
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description="ControlNet weights trained on sd-1.5 with scribble image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="softedge",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11p_sd15_softedge",
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description="Controlnet weights trained on sd-1.5 with soft edge conditioning",
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description="ControlNet weights trained on sd-1.5 with soft edge conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="shuffle",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11e_sd15_shuffle",
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description="Controlnet weights trained on sd-1.5 with shuffle image conditioning",
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description="ControlNet weights trained on sd-1.5 with shuffle image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="tile",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11f1e_sd15_tile",
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description="Controlnet weights trained on sd-1.5 with tiled image conditioning",
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description="ControlNet weights trained on sd-1.5 with tiled image conditioning",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="ip2p",
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base=BaseModelType.StableDiffusion1,
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source="lllyasviel/control_v11e_sd15_ip2p",
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description="Controlnet weights trained on sd-1.5 with ip2p conditioning.",
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description="ControlNet weights trained on sd-1.5 with ip2p conditioning.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="canny-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="xinsir/controlnet-canny-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
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source="xinsir/controlNet-canny-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 with canny conditioning, by Xinsir.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="depth-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="diffusers/controlnet-depth-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 with depth conditioning.",
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source="diffusers/controlNet-depth-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 with depth conditioning.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="softedge-dexined-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="SargeZT/controlnet-sd-xl-1.0-softedge-dexined",
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description="Controlnet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
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source="SargeZT/controlNet-sd-xl-1.0-softedge-dexined",
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description="ControlNet weights trained on sdxl-1.0 with dexined soft edge preprocessing.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="depth-16bit-zoe-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="SargeZT/controlnet-sd-xl-1.0-depth-16bit-zoe",
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description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
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source="SargeZT/controlNet-sd-xl-1.0-depth-16bit-zoe",
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description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (16 bits).",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="depth-zoe-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="diffusers/controlnet-zoe-depth-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
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source="diffusers/controlNet-zoe-depth-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 with Zoe's preprocessor (32 bits).",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="openpose-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="xinsir/controlnet-openpose-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
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source="xinsir/controlNet-openpose-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 compatible with the DWPose processor by Xinsir.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="scribble-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="xinsir/controlnet-scribble-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
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source="xinsir/controlNet-scribble-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 compatible with various lineart processors and black/white sketches by Xinsir.",
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type=ModelType.ControlNet,
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),
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StarterModel(
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name="tile-sdxl",
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base=BaseModelType.StableDiffusionXL,
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source="xinsir/controlnet-tile-sdxl-1.0",
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description="Controlnet weights trained on sdxl-1.0 with tiled image conditioning",
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source="xinsir/controlNet-tile-sdxl-1.0",
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description="ControlNet weights trained on sdxl-1.0 with tiled image conditioning",
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type=ModelType.ControlNet,
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),
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# endregion
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