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add sdxl.t2i_adapter.depth.zoe + rework mappings of t2i adapters
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9b19272d75
commit
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@ -120,6 +120,7 @@ def main() -> None:
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# SDXL T2I-Adapters
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t2iadapter_sdxl.canny.convert()
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t2iadapter_sdxl.depth_zoe.convert()
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# ELLA adapters
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ella.sd15_t5xl.convert()
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@ -4,27 +4,28 @@ from refiners.conversion.utils import Conversion, Hub, WeightRecipe
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diffusers_recipe = WeightRecipe(
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key_map={
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# first part
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"adapter.conv_in": "Conv2d",
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"adapter.body.0.resnets.0.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.0.resnets.1.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.0.resnets.0.block2": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.0.resnets.1.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.0.resnets.1.block2": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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"adapter.body.1.downsample": "StatefulResidualBlocks_2.ResidualBlocks.Downsample2d",
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"adapter.body.2.downsample": "StatefulResidualBlocks_3.ResidualBlocks.Downsample2d",
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"adapter.body.3.downsample": "StatefulResidualBlocks_4.ResidualBlocks.Downsample2d",
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# second part
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"adapter.body.1.in_conv": "StatefulResidualBlocks_2.ResidualBlocks.Conv2d",
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"adapter.body.1.resnets.0.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.1.resnets.1.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.1.resnets.0.block2": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.1.resnets.1.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.1.resnets.1.block2": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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# third part
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"adapter.body.2.in_conv": "StatefulResidualBlocks_3.ResidualBlocks.Conv2d",
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"adapter.body.2.resnets.0.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.2.resnets.1.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.3.resnets.0.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.3.resnets.1.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.2.resnets.0.block2": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.2.resnets.1.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.2.resnets.1.block2": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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# fourth part
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"adapter.body.3.resnets.0.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.3.resnets.0.block2": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.3.resnets.1.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.3.resnets.1.block2": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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},
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)
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@ -4,25 +4,28 @@ from refiners.conversion.utils import Conversion, Hub, WeightRecipe
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diffusers_recipe = WeightRecipe(
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key_map={
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# first part
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"adapter.conv_in": "Conv2d",
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"adapter.body.0.resnets.0.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.0.resnets.1.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.0.resnets.0.block2": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.0.resnets.1.block1": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.0.resnets.1.block2": "StatefulResidualBlocks_1.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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# second part
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"adapter.body.1.in_conv": "StatefulResidualBlocks_2.ResidualBlocks.Conv2d",
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"adapter.body.1.resnets.0.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.1.resnets.1.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.1.resnets.0.block2": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.1.resnets.1.block1": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.1.resnets.1.block2": "StatefulResidualBlocks_2.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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"adapter.body.2.downsample": "StatefulResidualBlocks_3.ResidualBlocks.Downsample2d",
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# third part
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"adapter.body.2.in_conv": "StatefulResidualBlocks_3.ResidualBlocks.Conv2d",
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"adapter.body.2.resnets.0.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.2.resnets.1.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.3.resnets.0.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.3.resnets.1.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.2.resnets.0.block2": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.2.resnets.1.block1": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.2.resnets.1.block2": "StatefulResidualBlocks_3.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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# fourth part
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"adapter.body.3.resnets.0.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_1",
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"adapter.body.3.resnets.0.block2": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_1.Conv2d_2",
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"adapter.body.3.resnets.1.block1": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_1",
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"adapter.body.3.resnets.1.block2": "StatefulResidualBlocks_4.ResidualBlocks.Chain.ResidualBlock_2.Conv2d_2",
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},
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)
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@ -42,3 +45,18 @@ canny = Conversion(
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recipe=diffusers_recipe,
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dtype=torch.float16,
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)
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depth_zoe = Conversion(
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original=Hub(
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repo_id="TencentARC/t2i-adapter-depth-zoe-sdxl-1.0",
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filename="diffusion_pytorch_model.safetensors",
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revision="d6282b3be9e0376d3fd0fd132959fdab143e2e51",
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expected_sha256="613884bf550bf6750f2f22cdb17bb92f49a148cad01fdd952118df4d386acd55",
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),
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converted=Hub(
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repo_id="refiners/sdxl.t2i_adapter.depth.zoe",
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filename="model.safetensors",
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expected_sha256="f7199c4c6b1f38bc50ed8c7cb6220a0fd09d18779c29044e28d8ff582e941f82",
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),
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recipe=diffusers_recipe,
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dtype=torch.float16,
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)
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