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kwonseungchan
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output_controlnet_pth_v1

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

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Files changed (21) hide show
  1. README.md +39 -0
  2. checkpoint-10000/controlnet/config.json +51 -0
  3. checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors +3 -0
  4. checkpoint-10000/optimizer.bin +3 -0
  5. checkpoint-10000/random_states_0.pkl +3 -0
  6. checkpoint-10000/scaler.pt +3 -0
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  8. checkpoint-15000/controlnet/config.json +51 -0
  9. checkpoint-15000/controlnet/diffusion_pytorch_model.safetensors +3 -0
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  11. checkpoint-15000/random_states_0.pkl +3 -0
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  14. checkpoint-5000/controlnet/config.json +51 -0
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  20. config.json +51 -0
  21. diffusion_pytorch_model.safetensors +3 -0
README.md ADDED
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+ ---
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+ license: creativeml-openrail-m
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+ library_name: diffusers
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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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+ base_model: runwayml/stable-diffusion-v1-5
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+ inference: true
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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-kwonseungchan/output_controlnet_pth_v1
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+
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+ These are controlnet weights trained on runwayml/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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+ "controlnet_conditioning_channel_order": "rgb",
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+ "cross_attention_dim": 768,
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+ "CrossAttnDownBlock2D",
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+ "CrossAttnDownBlock2D",
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