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SAGI-1
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SDXL-CANNY-CHECKPOINTS

Text-to-Image
Diffusers
Safetensors
stable-diffusion-xl
stable-diffusion-xl-diffusers
t2iadapter
diffusers-training
Model card Files Community
SAGI-1 commited on
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End of training

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  1. .gitattributes +1 -0
  2. .ipynb_checkpoints/config-checkpoint.json +15 -0
  3. README.md +42 -0
  4. checkpoint-11502/optimizer.bin +3 -0
  5. checkpoint-11502/random_states_0.pkl +3 -0
  6. checkpoint-11502/scaler.pt +3 -0
  7. checkpoint-11502/scheduler.bin +3 -0
  8. checkpoint-11502/t2iadapter/config.json +15 -0
  9. checkpoint-11502/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  10. checkpoint-13419/optimizer.bin +3 -0
  11. checkpoint-13419/random_states_0.pkl +3 -0
  12. checkpoint-13419/scaler.pt +3 -0
  13. checkpoint-13419/scheduler.bin +3 -0
  14. checkpoint-13419/t2iadapter/config.json +15 -0
  15. checkpoint-13419/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  16. checkpoint-15336/optimizer.bin +3 -0
  17. checkpoint-15336/random_states_0.pkl +3 -0
  18. checkpoint-15336/scaler.pt +3 -0
  19. checkpoint-15336/scheduler.bin +3 -0
  20. checkpoint-15336/t2iadapter/config.json +15 -0
  21. checkpoint-15336/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  22. checkpoint-17253/optimizer.bin +3 -0
  23. checkpoint-17253/random_states_0.pkl +3 -0
  24. checkpoint-17253/scaler.pt +3 -0
  25. checkpoint-17253/scheduler.bin +3 -0
  26. checkpoint-17253/t2iadapter/config.json +15 -0
  27. checkpoint-17253/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  28. checkpoint-1917/optimizer.bin +3 -0
  29. checkpoint-1917/random_states_0.pkl +3 -0
  30. checkpoint-1917/scaler.pt +3 -0
  31. checkpoint-1917/scheduler.bin +3 -0
  32. checkpoint-1917/t2iadapter/config.json +15 -0
  33. checkpoint-1917/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  34. checkpoint-19170/optimizer.bin +3 -0
  35. checkpoint-19170/random_states_0.pkl +3 -0
  36. checkpoint-19170/scaler.pt +3 -0
  37. checkpoint-19170/scheduler.bin +3 -0
  38. checkpoint-19170/t2iadapter/config.json +15 -0
  39. checkpoint-19170/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  40. checkpoint-21087/optimizer.bin +3 -0
  41. checkpoint-21087/random_states_0.pkl +3 -0
  42. checkpoint-21087/scaler.pt +3 -0
  43. checkpoint-21087/scheduler.bin +3 -0
  44. checkpoint-21087/t2iadapter/config.json +15 -0
  45. checkpoint-21087/t2iadapter/diffusion_pytorch_model.safetensors +3 -0
  46. checkpoint-23004/optimizer.bin +3 -0
  47. checkpoint-23004/random_states_0.pkl +3 -0
  48. checkpoint-23004/scaler.pt +3 -0
  49. checkpoint-23004/scheduler.bin +3 -0
  50. checkpoint-23004/t2iadapter/config.json +15 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ {
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+ "_class_name": "T2IAdapter",
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+ "_diffusers_version": "0.28.0.dev0",
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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-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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+ - t2iadapter
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+ - diffusers-training
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+ base_model: stabilityai/stable-diffusion-xl-base-1.0
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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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+ # t2iadapter-SAGI-1/output
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+
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+ These are t2iadapter weights trained on stabilityai/stable-diffusion-xl-base-1.0 with new type of conditioning.
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+ You can find some example images below.
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+ prompt: Design a circular logo for a boutique featuring rose gold, brush strokes, and glitter elements, exuding a feminine and luxurious atmosphere
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+ ![images_0)](./images_0.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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