Upload 15 files

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+ControlNet11/Animeline/controlnet11Models_animeline_0.png filter=lfs diff=lfs merge=lfs -text
+ControlNet11/Inpaint/controlnet11Models_inpaint_0.png filter=lfs diff=lfs merge=lfs -text
+ControlNet11/Lineart/controlnet11Models_lineart_0.png filter=lfs diff=lfs merge=lfs -text

ControlNet11/Animeline/controlnet11Models_animeline.civit.info

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ControlNet11/Animeline/controlnet11Models_animeline.safetensors

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ControlNet11/Animeline/controlnet11Models_animeline.yaml

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+model:
+  target: cldm.cldm.ControlLDM
+  params:
+    linear_start: 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

ControlNet11/Canny/controlnet11Models_canny.civit.full.info

@@ -0,0 +1 @@
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Place them alongside the models in the models folder - making sure they have the same name as the models!</strong><br /></p><p>These models are embedded with the neural network data required to make ControlNet function, they will <strong>not produce good images unless they are used with ControlNet</strong>.<br /><br />To be honest, there isn't much difference between these and the <a target=\"_blank\" rel=\"ugc\" href=\"https://civitai.com/models/9251/controlnet-pre-trained-models\">OG ControlNet V1's</a>. <strong>These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.</strong></p><p></p><ul><li><p>control_v11p_sd15_seg</p></li><li><p>control_v11p_sd15_softedge</p></li><li><p>control_v11p_sd15_normalbae</p></li><li><p>control_v11p_sd15_scribble</p></li><li><p>control_v11p_sd15_mlsd</p></li><li><p>control_v11p_sd15_openpose</p></li><li><p>control_v11p_sd15_depth</p></li><li><p>control_v11p_sd15_canny</p></li></ul><p></p><ul><li><p>control_v11e_sd15_ip2p</p></li><li><p>control_v11e_sd15_shuffle</p></li><li><p>control_v11p_sd15_inpaint</p></li><li><p>control_v11p_sd15_lineart</p></li><li><p>control_v11p_sd15s2_lineart_anime</p></li><li><p>control_v11u_sd15_tile</p></li></ul><p></p><p>Download these models and place them in the <code>\\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models</code> directory.<br /><br /><strong>Please consider joining my Patreon</strong>! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) <a target=\"_blank\" rel=\"ugc\" href=\"http://patreon.com/theally\">patreon.com/theally</a> - I also have a write-up of ControlNet and will be updating with the latest news/developments!</p>","type":"Controlnet","poi":false,"nsfw":false,"allowNoCredit":false,"allowCommercialUse":"RentCivit","allowDerivatives":false,"allowDifferentLicense":true,"stats":{"downloadCount":106632,"favoriteCount":2139,"commentCount":83,"ratingCount":29,"rating":5},"creator":{"username":"theally","image":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/79666644-f04c-4b0c-5d2d-ca8daafaee00/width=96/theally.jpeg"},"tags":["controlnet","tool","pruned","safetensors"],"modelVersions":[{"id":67566,"modelId":38784,"name":"Tile (e)","createdAt":"2023-05-11T00:27:55.243Z","updatedAt":"2023-05-11T11:17:54.226Z","trainedWords":[],"trainingStatus":null,"trainingDetails":null,"baseModel":"SD 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ControlNet11/Canny/controlnet11Models_canny.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8932b66e15aae835b3490dbf989f56c253104cee08a88bf21283762f557c9f10
+size 722601100

ControlNet11/Canny/controlnet11Models_canny.yaml

@@ -0,0 +1,79 @@
+model:
+  target: cldm.cldm.ControlLDM
+  params:
+    linear_start: 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

ControlNet11/Depth/controlnet11Models_depth.civit.full.info

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Place them alongside the models in the models folder - making sure they have the same name as the models!</strong><br /></p><p>These models are embedded with the neural network data required to make ControlNet function, they will <strong>not produce good images unless they are used with ControlNet</strong>.<br /><br />To be honest, there isn't much difference between these and the <a target=\"_blank\" rel=\"ugc\" href=\"https://civitai.com/models/9251/controlnet-pre-trained-models\">OG ControlNet V1's</a>. <strong>These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.</strong></p><p></p><ul><li><p>control_v11p_sd15_seg</p></li><li><p>control_v11p_sd15_softedge</p></li><li><p>control_v11p_sd15_normalbae</p></li><li><p>control_v11p_sd15_scribble</p></li><li><p>control_v11p_sd15_mlsd</p></li><li><p>control_v11p_sd15_openpose</p></li><li><p>control_v11p_sd15_depth</p></li><li><p>control_v11p_sd15_canny</p></li></ul><p></p><ul><li><p>control_v11e_sd15_ip2p</p></li><li><p>control_v11e_sd15_shuffle</p></li><li><p>control_v11p_sd15_inpaint</p></li><li><p>control_v11p_sd15_lineart</p></li><li><p>control_v11p_sd15s2_lineart_anime</p></li><li><p>control_v11u_sd15_tile</p></li></ul><p></p><p>Download these models and place them in the <code>\\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models</code> directory.<br /><br /><strong>Please consider joining my Patreon</strong>! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) <a target=\"_blank\" rel=\"ugc\" href=\"http://patreon.com/theally\">patreon.com/theally</a> - I also have a write-up of ControlNet and will be updating with the latest news/developments!</p>","type":"Controlnet","poi":false,"nsfw":false,"allowNoCredit":false,"allowCommercialUse":"RentCivit","allowDerivatives":false,"allowDifferentLicense":true,"stats":{"downloadCount":106632,"favoriteCount":2139,"commentCount":83,"ratingCount":29,"rating":5},"creator":{"username":"theally","image":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/79666644-f04c-4b0c-5d2d-ca8daafaee00/width=96/theally.jpeg"},"tags":["controlnet","tool","pruned","safetensors"],"modelVersions":[{"id":67566,"modelId":38784,"name":"Tile (e)","createdAt":"2023-05-11T00:27:55.243Z","updatedAt":"2023-05-11T11:17:54.226Z","trainedWords":[],"trainingStatus":null,"trainingDetails":null,"baseModel":"SD 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ControlNet11/Inpaint/controlnet11Models_inpaint.yaml

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+    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

ControlNet11/Lineart/controlnet11Models_lineart.civit.full.info

@@ -0,0 +1 @@
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Place them alongside the models in the models folder - making sure they have the same name as the models!</strong><br /></p><p>These models are embedded with the neural network data required to make ControlNet function, they will <strong>not produce good images unless they are used with ControlNet</strong>.<br /><br />To be honest, there isn't much difference between these and the <a target=\"_blank\" rel=\"ugc\" href=\"https://civitai.com/models/9251/controlnet-pre-trained-models\">OG ControlNet V1's</a>. <strong>These models are further trained ControlNet 1.0 models, with an additional 200 GPU hours on an A100 80G.</strong></p><p></p><ul><li><p>control_v11p_sd15_seg</p></li><li><p>control_v11p_sd15_softedge</p></li><li><p>control_v11p_sd15_normalbae</p></li><li><p>control_v11p_sd15_scribble</p></li><li><p>control_v11p_sd15_mlsd</p></li><li><p>control_v11p_sd15_openpose</p></li><li><p>control_v11p_sd15_depth</p></li><li><p>control_v11p_sd15_canny</p></li></ul><p></p><ul><li><p>control_v11e_sd15_ip2p</p></li><li><p>control_v11e_sd15_shuffle</p></li><li><p>control_v11p_sd15_inpaint</p></li><li><p>control_v11p_sd15_lineart</p></li><li><p>control_v11p_sd15s2_lineart_anime</p></li><li><p>control_v11u_sd15_tile</p></li></ul><p></p><p>Download these models and place them in the <code>\\stable-diffusion-webui\\extensions\\sd-webui-controlnet\\models</code> directory.<br /><br /><strong>Please consider joining my Patreon</strong>! Advanced SD tutorials, settings explanations, adult-art, from a female content creator (me!) <a target=\"_blank\" rel=\"ugc\" href=\"http://patreon.com/theally\">patreon.com/theally</a> - I also have a write-up of ControlNet and will be updating with the latest news/developments!</p>","type":"Controlnet","poi":false,"nsfw":false,"allowNoCredit":false,"allowCommercialUse":"RentCivit","allowDerivatives":false,"allowDifferentLicense":true,"stats":{"downloadCount":106637,"favoriteCount":2139,"commentCount":83,"ratingCount":29,"rating":5},"creator":{"username":"theally","image":"https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/79666644-f04c-4b0c-5d2d-ca8daafaee00/width=96/theally.jpeg"},"tags":["controlnet","tool","pruned","safetensors"],"modelVersions":[{"id":67566,"modelId":38784,"name":"Tile (e)","createdAt":"2023-05-11T00:27:55.243Z","updatedAt":"2023-05-11T11:17:54.226Z","trainedWords":[],"trainingStatus":null,"trainingDetails":null,"baseModel":"SD 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+    linear_end: 0.0120
+    num_timesteps_cond: 1
+    log_every_t: 200
+    timesteps: 1000
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+    control_key: "hint"
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+    channels: 4
+    cond_stage_trainable: false
+    conditioning_key: crossattn
+    monitor: val/loss_simple_ema
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+    use_ema: False
+    only_mid_control: False
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+        hint_channels: 3
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+        use_checkpoint: True
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+        out_channels: 4
+        model_channels: 320
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+        num_heads: 8
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+        use_checkpoint: True
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+      params:
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+        monitor: val/rec_loss
+        ddconfig:
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+          z_channels: 4
+          resolution: 256
+          in_channels: 3
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+          ch: 128
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