End of training

README.md

@@ -15,8 +15,8 @@ inference: true
 
 These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with new type of conditioning.
 You can find some example images below.
-prompt: red circle with blue background
+prompt: there are some very tall rocks in the desert with trees
 ![images_0)](./images_0.png)
-prompt: cyan circle with brown floral background
+prompt: araffe on a cruise ship with a pool and people on deck
 ![images_1)](./images_1.png)
 

checkpoint-500/controlnet/config.json

@@ -0,0 +1,42 @@
+{
+  "_class_name": "ControlNetModel",
+  "_diffusers_version": "0.18.0.dev0",
+  "act_fn": "silu",
+  "attention_head_dim": 8,
+  "block_out_channels": [
+    320,
+    640,
+    1280,
+    1280
+  ],
+  "class_embed_type": null,
+  "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,
+  "flip_sin_to_cos": true,
+  "freq_shift": 0,
+  "global_pool_conditions": false,
+  "in_channels": 4,
+  "layers_per_block": 2,
+  "mid_block_scale_factor": 1,
+  "norm_eps": 1e-05,
+  "norm_num_groups": 32,
+  "num_class_embeds": null,
+  "only_cross_attention": false,
+  "projection_class_embeddings_input_dim": null,
+  "resnet_time_scale_shift": "default",
+  "upcast_attention": false,
+  "use_linear_projection": false
+}

checkpoint-500/controlnet/diffusion_pytorch_model.bin

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checkpoint-500/optimizer.bin

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checkpoint-500/random_states_0.pkl

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checkpoint-500/scheduler.bin

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+size 563

diffusion_pytorch_model.bin

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 size 1445259705