End of training

.gitattributes

@@ -33,3 +33,4 @@ 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
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+images_0.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,43 @@
+---
+base_model: ButterChicken98/dec_logs_ab_v4_balanced
+library_name: diffusers
+license: creativeml-openrail-m
+inference: true
+tags:
+- stable-diffusion
+- stable-diffusion-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-ButterChicken98/bact_puls_controlnet_seg_v1
+
+These are controlnet weights trained on ButterChicken98/dec_logs_ab_v4_balanced with new type of conditioning.
+You can find some example images below.
+
+prompt: A soybean leaf in early infection of Bacterial Pustule, with tiny raised yellow-brown spots near the edges.
+![images_0)](./images_0.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]

checkpoint-3000/controlnet/config.json

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+  "_class_name": "ControlNetModel",
+  "_diffusers_version": "0.37.0.dev0",
+  "_name_or_path": "lllyasviel/control_v11p_sd15_seg",
+  "act_fn": "silu",
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+  "attention_head_dim": 8,
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+    640,
+    1280,
+    1280
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+  "conditioning_channels": 3,
+  "conditioning_embedding_out_channels": [
+    16,
+    32,
+    96,
+    256
+  ],
+  "controlnet_conditioning_channel_order": "rgb",
+  "cross_attention_dim": 768,
+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
+  "downsample_padding": 1,
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+  "flip_sin_to_cos": true,
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+  "in_channels": 4,
+  "layers_per_block": 2,
+  "mid_block_scale_factor": 1,
+  "mid_block_type": "UNetMidBlock2DCrossAttn",
+  "norm_eps": 1e-05,
+  "norm_num_groups": 32,
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+  "only_cross_attention": false,
+  "projection_class_embeddings_input_dim": null,
+  "resnet_time_scale_shift": "default",
+  "transformer_layers_per_block": 1,
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

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checkpoint-4000/controlnet/config.json

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+  "_class_name": "ControlNetModel",
+  "_diffusers_version": "0.37.0.dev0",
+  "_name_or_path": "lllyasviel/control_v11p_sd15_seg",
+  "act_fn": "silu",
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+  "conditioning_channels": 3,
+  "conditioning_embedding_out_channels": [
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+    96,
+    256
+  ],
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+  "cross_attention_dim": 768,
+  "down_block_types": [
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
+    "DownBlock2D"
+  ],
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+  "resnet_time_scale_shift": "default",
+  "transformer_layers_per_block": 1,
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

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checkpoint-5000/controlnet/config.json

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+  "_diffusers_version": "0.37.0.dev0",
+  "_name_or_path": "lllyasviel/control_v11p_sd15_seg",
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+    "CrossAttnDownBlock2D",
+    "CrossAttnDownBlock2D",
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config.json

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+  "act_fn": "silu",
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