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End of training

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  1. README.md +21 -0
  2. checkpoint-1000/optimizer.bin +3 -0
  3. checkpoint-1000/pytorch_model.bin +3 -0
  4. checkpoint-1000/random_states_0.pkl +3 -0
  5. checkpoint-1000/scaler.pt +3 -0
  6. checkpoint-1000/scheduler.bin +3 -0
  7. checkpoint-10000/optimizer.bin +3 -0
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  9. checkpoint-10000/random_states_0.pkl +3 -0
  10. checkpoint-10000/scaler.pt +3 -0
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  12. checkpoint-10500/optimizer.bin +3 -0
  13. checkpoint-10500/pytorch_model.bin +3 -0
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  15. checkpoint-10500/scaler.pt +3 -0
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  17. checkpoint-11000/optimizer.bin +3 -0
  18. checkpoint-11000/pytorch_model.bin +3 -0
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  22. checkpoint-11500/optimizer.bin +3 -0
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  24. checkpoint-11500/random_states_0.pkl +3 -0
  25. checkpoint-11500/scaler.pt +3 -0
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  27. checkpoint-12000/optimizer.bin +3 -0
  28. checkpoint-12000/pytorch_model.bin +3 -0
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  30. checkpoint-12000/scaler.pt +3 -0
  31. checkpoint-12000/scheduler.bin +3 -0
  32. checkpoint-12500/optimizer.bin +3 -0
  33. checkpoint-12500/pytorch_model.bin +3 -0
  34. checkpoint-12500/random_states_0.pkl +3 -0
  35. checkpoint-12500/scaler.pt +3 -0
  36. checkpoint-12500/scheduler.bin +3 -0
  37. checkpoint-13000/optimizer.bin +3 -0
  38. checkpoint-13000/pytorch_model.bin +3 -0
  39. checkpoint-13000/random_states_0.pkl +3 -0
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  42. checkpoint-13500/optimizer.bin +3 -0
  43. checkpoint-13500/pytorch_model.bin +3 -0
  44. checkpoint-13500/random_states_0.pkl +3 -0
  45. checkpoint-13500/scaler.pt +3 -0
  46. checkpoint-13500/scheduler.bin +3 -0
  47. checkpoint-14000/optimizer.bin +3 -0
  48. checkpoint-14000/pytorch_model.bin +3 -0
  49. checkpoint-14000/random_states_0.pkl +3 -0
  50. checkpoint-14000/scaler.pt +3 -0
README.md ADDED
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+
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: runwayml/stable-diffusion-v1-5
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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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+
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+ # LoRA text2image fine-tuning - sanctia/lora-sd-finesse
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+ These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the None dataset. You can find some example images in the following.
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+
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+ ![img_0](./image_0.png)
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+ ![img_1](./image_1.png)
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+ ![img_2](./image_2.png)
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+ ![img_3](./image_3.png)
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+
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