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egbert-2x-source-bilinear

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  1. README.md +22 -0
  2. checkpoint-100/custom_checkpoint_0.pkl +3 -0
  3. checkpoint-100/optimizer.bin +3 -0
  4. checkpoint-100/pytorch_model.bin +3 -0
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  14. checkpoint-200/custom_checkpoint_0.pkl +3 -0
  15. checkpoint-200/optimizer.bin +3 -0
  16. checkpoint-200/pytorch_model.bin +3 -0
  17. checkpoint-200/random_states_0.pkl +3 -0
  18. checkpoint-200/scaler.pt +3 -0
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  20. checkpoint-300/custom_checkpoint_0.pkl +3 -0
  21. checkpoint-300/optimizer.bin +3 -0
  22. checkpoint-300/pytorch_model.bin +3 -0
  23. checkpoint-300/random_states_0.pkl +3 -0
  24. checkpoint-300/scaler.pt +3 -0
  25. checkpoint-300/scheduler.bin +3 -0
  26. checkpoint-400/custom_checkpoint_0.pkl +3 -0
  27. checkpoint-400/optimizer.bin +3 -0
  28. checkpoint-400/pytorch_model.bin +3 -0
  29. checkpoint-400/random_states_0.pkl +3 -0
  30. checkpoint-400/scaler.pt +3 -0
  31. checkpoint-400/scheduler.bin +3 -0
  32. checkpoint-500/custom_checkpoint_0.pkl +3 -0
  33. checkpoint-500/optimizer.bin +3 -0
  34. checkpoint-500/pytorch_model.bin +3 -0
  35. checkpoint-500/random_states_0.pkl +3 -0
  36. checkpoint-500/scaler.pt +3 -0
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  38. checkpoint-600/custom_checkpoint_0.pkl +3 -0
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  44. checkpoint-700/custom_checkpoint_0.pkl +3 -0
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  46. checkpoint-700/pytorch_model.bin +3 -0
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  50. checkpoint-800/custom_checkpoint_0.pkl +3 -0
README.md ADDED
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: stabilityai/stable-diffusion-2-1-base
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+ instance_prompt: egbert
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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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+ - lora
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+ inference: true
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+ ---
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+ # LoRA DreamBooth - egbert-2x-source-bilinear
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+
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+ These are LoRA adaption weights for [stabilityai/stable-diffusion-2-1-base](https://huggingface.co/stabilityai/stable-diffusion-2-1-base). The weights were trained on the instance prompt "egbert" using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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+
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+ Test prompt: egbert
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+ ![image_0](test_images/image_0.png)
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+ ![image_1](test_images/image_1.png)
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+ ![image_2](test_images/image_2.png)
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+ ![image_3](test_images/image_3.png)
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+
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