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--- a/.gitattributes
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@@ -33,3 +33,8 @@ 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
+images_0.png filter=lfs diff=lfs merge=lfs -text
+images_1.png filter=lfs diff=lfs merge=lfs -text
+images_2.png filter=lfs diff=lfs merge=lfs -text
+images_3.png filter=lfs diff=lfs merge=lfs -text
+images_4.png filter=lfs diff=lfs merge=lfs -text
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..5a60d7d5948a240d9a766b80ec7eb147ab09d6e8
--- /dev/null
+++ b/README.md
@@ -0,0 +1,51 @@
+---
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+library_name: diffusers
+license: openrail++
+inference: true
+tags:
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+- text-to-image
+- diffusers
+- controlnet
+- diffusers-training
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# controlnet-sarcastitva/animgseg_v2
+
+These are controlnet weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.
+You can find some example images below.
+
+prompt: face of a cartoon character drawn by a kid, creative, highres
+![images_0)](./images_0.png)
+prompt: face of a cartoon character drawn by a kid, crayon art
+![images_1)](./images_1.png)
+prompt: face of a cartoon character drawn by a kid, line art
+![images_2)](./images_2.png)
+prompt: face of a cartoon character drawn by a kid, watercolor painting
+![images_3)](./images_3.png)
+prompt: face of a cartoon character drawn by a kid, stencil and charcoal art
+![images_4)](./images_4.png)
+
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]
\ No newline at end of file
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+{
+  "_class_name": "ControlNetModel",
+  "_diffusers_version": "0.32.0.dev0",
+  "act_fn": "silu",
+  "addition_embed_type": "text_time",
+  "addition_embed_type_num_heads": 64,
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+    5,
+    10,
+    20
+  ],
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+    320,
+    640,
+    1280
+  ],
+  "class_embed_type": null,
+  "conditioning_channels": 3,
+  "conditioning_embedding_out_channels": [
+    16,
+    32,
+    96,
+    256
+  ],
+  "controlnet_conditioning_channel_order": "rgb",
+  "cross_attention_dim": 2048,
+  "down_block_types": [
+    "DownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D"
+  ],
+  "downsample_padding": 1,
+  "encoder_hid_dim": null,
+  "encoder_hid_dim_type": null,
+  "flip_sin_to_cos": true,
+  "freq_shift": 0,
+  "global_pool_conditions": false,
+  "in_channels": 4,
+  "layers_per_block": 2,
+  "mid_block_scale_factor": 1,
+  "mid_block_type": "UNetMidBlock2DCrossAttn",
+  "norm_eps": 1e-05,
+  "norm_num_groups": 32,
+  "num_attention_heads": null,
+  "num_class_embeds": null,
+  "only_cross_attention": false,
+  "projection_class_embeddings_input_dim": 2816,
+  "resnet_time_scale_shift": "default",
+  "transformer_layers_per_block": [
+    1,
+    2,
+    10
+  ],
+  "upcast_attention": null,
+  "use_linear_projection": true
+}
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+  "cross_attention_dim": 2048,
+  "down_block_types": [
+    "DownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D"
+  ],
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+    10
+  ],
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+  "use_linear_projection": true
+}
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+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D"
+  ],
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+    1,
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+    10
+  ],
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+  "use_linear_projection": true
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+    1,
+    2,
+    10
+  ],
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+  "use_linear_projection": true
+}
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+    1,
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+    10
+  ],
+  "upcast_attention": null,
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