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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 realismEngine_v10.preview.png filter=lfs diff=lfs merge=lfs -text
+realisticVisionV13_v13-inpainting.preview.png filter=lfs diff=lfs merge=lfs -text

realisticVisionV13_v13-inpainting.civitai.info

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+{
+    "id": 7935,
+    "modelId": 4201,
+    "name": "V1.3-inpainting",
+    "createdAt": "2023-02-05T06:36:50.061Z",
+    "updatedAt": "2023-03-06T07:36:34.827Z",
+    "trainedWords": [
+        "analog style",
+        "modelshoot style",
+        "nsfw",
+        "nudity"
+    ],
+    "baseModel": "SD 1.5",
+    "earlyAccessTimeFrame": 0,
+    "description": "<p><strong><u>NOT FOR TRAINING!</u></strong></p><p>Model for <strong>inpainting</strong> and <strong>outpainting</strong>.<br />Make sure that the model name has the ending <strong>-inpainting </strong>and config file has the same name as the model.</p><ul><li><p>vae-ft-mse-840000-ema-pruned.ckpt included</p></li></ul>",
+    "model": {
+        "name": "Realistic Vision V1.3 - Fantasy.ai",
+        "type": "Checkpoint",
+        "nsfw": false,
+        "poi": false
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realisticVisionV13_v13-inpainting.safetensors

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realisticVisionV13_v13-inpainting.yaml

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+model:
+  base_learning_rate: 7.5e-05
+  target: ldm.models.diffusion.ddpm.LatentInpaintDiffusion
+  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"
+    image_size: 64
+    channels: 4
+    cond_stage_trainable: false   # Note: different from the one we trained before
+    conditioning_key: hybrid   # important
+    monitor: val/loss_simple_ema
+    scale_factor: 0.18215
+    finetune_keys: null
+
+    scheduler_config: # 10000 warmup steps
+      target: ldm.lr_scheduler.LambdaLinearScheduler
+      params:
+        warm_up_steps: [ 2500 ] # NOTE for resuming. use 10000 if starting from scratch
+        cycle_lengths: [ 10000000000000 ] # incredibly large number to prevent corner cases
+        f_start: [ 1.e-6 ]
+        f_max: [ 1. ]
+        f_min: [ 1. ]
+
+    unet_config:
+      target: ldm.modules.diffusionmodules.openaimodel.UNetModel
+      params:
+        image_size: 32 # unused
+        in_channels: 9  # 4 data + 4 downscaled image + 1 mask
+        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

realisticVisionV13_v13.civitai.info

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