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louistichelman
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controlnet_streetview_canny_350.300

Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
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  1. README.md +49 -0
  2. checkpoint-10000/controlnet/config.json +51 -0
  3. checkpoint-10000/controlnet/diffusion_pytorch_model.safetensors +3 -0
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  32. config.json +51 -0
  33. diffusion_pytorch_model.safetensors +3 -0
  34. image_control.png +0 -0
  35. images_0.png +0 -0
  36. images_1.png +0 -0
  37. images_2.png +0 -0
  38. images_3.png +0 -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-louistichelman/controlnet_streetview_canny_350.300
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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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+ You can find some example images below.
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+
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+ prompt: A google streetview image that shows a urban scene with a beauty-score of 31.616573, where scores are between 10 and 40 and higher scores indicate more beauty.
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+ ![images_0)](./images_0.png)
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+ prompt: A google streetview image that shows a urban scene with a beauty-score of 39.616564, where scores are between 10 and 40 and higher scores indicate more beauty.
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+ ![images_1)](./images_1.png)
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+ prompt: A google streetview image that shows a urban scene with a beauty-score of 23.188663, where scores are between 10 and 40 and higher scores indicate more beauty.
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+ ![images_2)](./images_2.png)
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+ prompt: A google streetview image that shows a urban scene with a beauty-score of 36.188663, where scores are between 10 and 40 and higher scores indicate more beauty.
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+ ![images_3)](./images_3.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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