These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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0.00085 + linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_animeline_0.png b/ControlNet11/controlnet11Models_animeline_0.png new file mode 100644 index 0000000000000000000000000000000000000000..36052c67213f64ae0dba4aec749d684f7204d140 --- /dev/null +++ b/ControlNet11/controlnet11Models_animeline_0.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9679bd8f70a957ba4e51e04a39f5d50c137505f4ee8798976e29fb41666fb9ec +size 1161218 diff --git a/ControlNet11/controlnet11Models_canny.civit.full.info b/ControlNet11/controlnet11Models_canny.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..4d7d18b51616b0806040d296f0e1951a9340dfba --- /dev/null +++ b/ControlNet11/controlnet11Models_canny.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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0.00085 + linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_canny_0.jpeg b/ControlNet11/controlnet11Models_canny_0.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..dfcaedc415644a2d6db7586a6c926aa06c3c5d5f Binary files /dev/null and b/ControlNet11/controlnet11Models_canny_0.jpeg differ diff --git a/ControlNet11/controlnet11Models_canny_1.jpeg b/ControlNet11/controlnet11Models_canny_1.jpeg new file mode 100644 index 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Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_inpaint_0.png b/ControlNet11/controlnet11Models_inpaint_0.png new file mode 100644 index 0000000000000000000000000000000000000000..3b78a8d4a3a40ddcd385f279fc1800f559414b7d --- /dev/null +++ b/ControlNet11/controlnet11Models_inpaint_0.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f9b38a8d362d9b13e2e555081399bd25a72f8ce081f9e5db8087aa67d8e8881 +size 1190629 diff --git a/ControlNet11/controlnet11Models_lineart.civit.full.info b/ControlNet11/controlnet11Models_lineart.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_lineart.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_lineart_0.png b/ControlNet11/controlnet11Models_lineart_0.png new file mode 100644 index 0000000000000000000000000000000000000000..f7c50b719b8b167d257c390d4b8331887e704f98 --- /dev/null +++ b/ControlNet11/controlnet11Models_lineart_0.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e43ad68e06ed57769004ac82306dba44d6f67e3254643a56ff887b30a56b7119 +size 1298451 diff --git a/ControlNet11/controlnet11Models_mlsd.civit.full.info b/ControlNet11/controlnet11Models_mlsd.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_mlsd.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git 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file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_normal.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_openpose_0.jpeg b/ControlNet11/controlnet11Models_openpose_0.jpeg new file mode 100644 index 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Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_pix2pix_0.png b/ControlNet11/controlnet11Models_pix2pix_0.png new file mode 100644 index 0000000000000000000000000000000000000000..5b67875699a42f054090437f71ffcf0d5df33a5e --- /dev/null +++ b/ControlNet11/controlnet11Models_pix2pix_0.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:84d8c5fd0ad8f5ae9b65836800570a0d3a0c1947d4e10008ecfc6c708a776de4 +size 1230110 diff --git a/ControlNet11/controlnet11Models_scribble.civit.full.info b/ControlNet11/controlnet11Models_scribble.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_scribble.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_scribble_0.jpeg b/ControlNet11/controlnet11Models_scribble_0.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..109d67c355b8615e610c092842747a4f5e5a927d Binary files /dev/null and b/ControlNet11/controlnet11Models_scribble_0.jpeg differ diff --git a/ControlNet11/controlnet11Models_scribble_1.jpeg b/ControlNet11/controlnet11Models_scribble_1.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..34f745f0d6199f913cb23f177f21c807fe4011cf Binary files /dev/null and b/ControlNet11/controlnet11Models_scribble_1.jpeg differ diff --git a/ControlNet11/controlnet11Models_seg.civit.full.info b/ControlNet11/controlnet11Models_seg.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_seg.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: 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b/ControlNet11/controlnet11Models_shuffle.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..4d7d18b51616b0806040d296f0e1951a9340dfba --- /dev/null +++ b/ControlNet11/controlnet11Models_shuffle.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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linear_end: 0.0120 + num_timesteps_cond: 1 + log_every_t: 200 + timesteps: 1000 + first_stage_key: "jpg" + cond_stage_key: "txt" + control_key: "hint" + image_size: 64 + channels: 4 + cond_stage_trainable: false + conditioning_key: crossattn + monitor: val/loss_simple_ema + scale_factor: 0.18215 + use_ema: False + only_mid_control: False + global_average_pooling: True + + control_stage_config: + target: cldm.cldm.ControlNet + params: + image_size: 32 # unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_shuffle_0.png b/ControlNet11/controlnet11Models_shuffle_0.png new file mode 100644 index 0000000000000000000000000000000000000000..314907a1a00b9b4f1b70dc3d4b4868c22b6c7a98 --- /dev/null +++ b/ControlNet11/controlnet11Models_shuffle_0.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2164fd256d8a35957296435f27c667e0131005b6efd6a8bbe44101fe07e0dbec +size 1707050 diff --git a/ControlNet11/controlnet11Models_softedge.civit.full.info b/ControlNet11/controlnet11Models_softedge.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..4d7d18b51616b0806040d296f0e1951a9340dfba --- /dev/null +++ b/ControlNet11/controlnet11Models_softedge.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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unused + in_channels: 4 + hint_channels: 3 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + unet_config: + target: cldm.cldm.ControlledUnetModel + params: + image_size: 32 # unused + in_channels: 4 + out_channels: 4 + model_channels: 320 + attention_resolutions: [ 4, 2, 1 ] + num_res_blocks: 2 + channel_mult: [ 1, 2, 4, 4 ] + num_heads: 8 + use_spatial_transformer: True + transformer_depth: 1 + context_dim: 768 + use_checkpoint: True + legacy: False + + first_stage_config: + target: ldm.models.autoencoder.AutoencoderKL + params: + embed_dim: 4 + monitor: val/rec_loss + ddconfig: + double_z: true + z_channels: 4 + resolution: 256 + in_channels: 3 + out_ch: 3 + ch: 128 + ch_mult: + - 1 + - 2 + - 4 + - 4 + num_res_blocks: 2 + attn_resolutions: [] + dropout: 0.0 + lossconfig: + target: torch.nn.Identity + + cond_stage_config: + target: ldm.modules.encoders.modules.FrozenCLIPEmbedder diff --git a/ControlNet11/controlnet11Models_softedge_0.jpeg b/ControlNet11/controlnet11Models_softedge_0.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..e21c09ea0ff4dd8916829e1df66097b607d510cb Binary files /dev/null and b/ControlNet11/controlnet11Models_softedge_0.jpeg differ diff --git a/ControlNet11/controlnet11Models_softedge_1.jpeg b/ControlNet11/controlnet11Models_softedge_1.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..e1cfc202a0f945da02d4a7d3d3eb929eb0d6c3d1 Binary files /dev/null and b/ControlNet11/controlnet11Models_softedge_1.jpeg differ diff --git a/ControlNet11/controlnet11Models_softedge_2.jpeg b/ControlNet11/controlnet11Models_softedge_2.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..83b49f10f245645256e3dad056dd1ebc9a055afd Binary files /dev/null and b/ControlNet11/controlnet11Models_softedge_2.jpeg differ diff --git a/ControlNet11/controlnet11Models_tileE.civit.full.info b/ControlNet11/controlnet11Models_tileE.civit.full.info new file mode 100644 index 0000000000000000000000000000000000000000..8a9e44fbbce8a16d70fcd40395ce37a2042735b6 --- /dev/null +++ b/ControlNet11/controlnet11Models_tileE.civit.full.info @@ -0,0 +1 @@ +{"id":38784,"name":"ControlNet 1.1 Models","description":"These are the new ControlNet 1.1 models required for the ControlNet extension, converted to Safetensor and \"pruned\" to extract the ControlNet neural network.
Also Note: There are associated .yaml files for each of these models now. Place them alongside the models in the models folder - making sure they have the same name as the models!
These models are embedded with the neural network data required to make ControlNet function, they will not produce good images unless they are used with ControlNet.
To be honest, there isn't much difference between these and the OG ControlNet V1's. These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.
control_v11p_sd15_seg
control_v11p_sd15_softedge
control_v11p_sd15_normalbae
control_v11p_sd15_scribble
control_v11p_sd15_mlsd
control_v11p_sd15_openpose
control_v11p_sd15_depth
control_v11p_sd15_canny
control_v11e_sd15_ip2p
control_v11e_sd15_shuffle
control_v11p_sd15_inpaint
control_v11p_sd15_lineart
control_v11p_sd15s2_lineart_anime
control_v11u_sd15_tile
Download these models and place them in the \\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models directory.
Please consider joining my Patreon! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) patreon.com/theally - I also have a write-up of ControlNet and will be updating with the latest news/developments!
This is the \"e\" version of Tile - the latest version
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