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  1. README.md +47 -0
  2. checkpoint-10000/controlnet/config.json +57 -0
  3. checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors +3 -0
  4. checkpoint-10000/optimizer.bin +3 -0
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  6. checkpoint-10000/scaler.pt +3 -0
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  8. checkpoint-20000/controlnet/config.json +57 -0
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  14. config.json +57 -0
  15. diffusion_pytorch_model.safetensors +3 -0
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  17. images_1.png +0 -0
  18. images_2.png +0 -0
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README.md ADDED
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+ ---
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+ base_model: SG161222/RealVisXL_V3.0
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+ library_name: diffusers
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+ license: openrail++
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+ inference: true
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+ tags:
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+ - stable-diffusion-xl
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+ - stable-diffusion-xl-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-kwanY/EAS2
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+
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+ These are AlignNet weights trained on SG161222/RealVisXL_V3.0 with Pose, Expression and Sparse landmark conditions.
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+ You can find some example images below.
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+
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+ prompt: photo of a human
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+ ![images_0)](./images_0.png)
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+ prompt: A render of a head of Disney character
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+ ![images_1)](./images_1.png)
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+ prompt: a FHD head of an Orc
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+ ![images_2)](./images_2.png)
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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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