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algorithmist-girl
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generated_images_controlnet

Text-to-Image
Diffusers
TensorBoard
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
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End of training

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  1. README.md +39 -0
  2. config.json +51 -0
  3. diffusion_pytorch_model.safetensors +3 -0
  4. logs/train_controlnet/1733083445.2085192/events.out.tfevents.1733083445.520ebfb9cace.29583.1 +3 -0
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  48. logs/train_controlnet/events.out.tfevents.1733089031.b8de8dd3f2b9.8036.0 +3 -0
  49. logs/train_controlnet/events.out.tfevents.1733089073.b8de8dd3f2b9.8365.0 +3 -0
  50. logs/train_controlnet/events.out.tfevents.1733089286.b8de8dd3f2b9.9312.0 +3 -0
README.md ADDED
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+ ---
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+ base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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+ inference: true
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+ tags:
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - text-to-image
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+ - diffusers
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+ - controlnet
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+ - diffusers-training
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the training script had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+
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+ # controlnet-algorithmist-girl/generated_images_controlnet
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+
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+ These are controlnet weights trained on stable-diffusion-v1-5/stable-diffusion-v1-5 with new type of conditioning.
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+
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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+ ```python
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+ # TODO: add an example code snippet for running this diffusion pipeline
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+ ```
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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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+ {
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+ "conditioning_embedding_out_channels": [
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+ 256
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+ ],
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+ "controlnet_conditioning_channel_order": "rgb",
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+ "cross_attention_dim": 768,
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+ "down_block_types": [
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+ "CrossAttnDownBlock2D",
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+ "CrossAttnDownBlock2D",
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+ "CrossAttnDownBlock2D",
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+ "DownBlock2D"
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+ ],
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+ "downsample_padding": 1,
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+ "flip_sin_to_cos": true,
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+ "in_channels": 4,
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+ "layers_per_block": 2,
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+ "mid_block_scale_factor": 1,
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+ "mid_block_type": "UNetMidBlock2DCrossAttn",
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+ "norm_eps": 1e-05,
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+ "upcast_attention": false,
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+ "use_linear_projection": false
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+ }
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