End of training

README.md

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+---
+base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
+library_name: diffusers
+license: creativeml-openrail-m
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- controlnet
+- diffusers-training
+inference: true
+---
+
+<!-- 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-maxpmx/output_smlm
+
+These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning.
+You can find some example images below.
+
+prompt: Denoise
+![images_0)](./images_0.png)
+prompt: Denoise
+![images_1)](./images_1.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-5000/controlnet/config.json

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+{
+ "_class_name": "ControlNetModel",
+ "_diffusers_version": "0.31.0.dev0",
+ "act_fn": "silu",
+ "addition_embed_type": null,
+ "addition_embed_type_num_heads": 64,
+ "addition_time_embed_dim": null,
+ "attention_head_dim": 8,
+ "block_out_channels": [
+ 320,
+ 640,
+ 1280,
+ 1280
+ ],
+ "class_embed_type": null,
+ "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,
+ "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": null,
+ "resnet_time_scale_shift": "default",
+ "transformer_layers_per_block": 1,
+ "upcast_attention": false,
+ "use_linear_projection": false
+}

checkpoint-5000/controlnet/diffusion_pytorch_model.safetensors

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checkpoint-5000/optimizer.bin

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checkpoint-5000/random_states_0.pkl

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checkpoint-5000/scaler.pt

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checkpoint-5000/scheduler.bin

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config.json

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+{
+ "_class_name": "ControlNetModel",
+ "_diffusers_version": "0.31.0.dev0",
+ "act_fn": "silu",
+ "addition_embed_type": null,
+ "addition_embed_type_num_heads": 64,
+ "addition_time_embed_dim": null,
+ "attention_head_dim": 8,
+ "block_out_channels": [
+ 320,
+ 640,
+ 1280,
+ 1280
+ ],
+ "class_embed_type": null,
+ "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,
+ "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": null,
+ "resnet_time_scale_shift": "default",
+ "transformer_layers_per_block": 1,
+ "upcast_attention": false,
+ "use_linear_projection": false
+}

diffusion_pytorch_model.safetensors

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