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End of training

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  1. README.md +43 -0
  2. checkpoint-10000/model.safetensors +3 -0
  3. checkpoint-10000/optimizer.bin +3 -0
  4. checkpoint-10000/pytorch_lora_weights.safetensors +3 -0
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  9. checkpoint-12000/pytorch_lora_weights.safetensors +3 -0
  10. checkpoint-12000/random_states_0.pkl +3 -0
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  14. checkpoint-14000/pytorch_lora_weights.safetensors +3 -0
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  19. checkpoint-2000/pytorch_lora_weights.safetensors +3 -0
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  21. checkpoint-2000/scheduler.bin +3 -0
  22. checkpoint-4000/model.safetensors +3 -0
  23. checkpoint-4000/optimizer.bin +3 -0
  24. checkpoint-4000/pytorch_lora_weights.safetensors +3 -0
  25. checkpoint-4000/random_states_0.pkl +3 -0
  26. checkpoint-4000/scheduler.bin +3 -0
  27. checkpoint-6000/model.safetensors +3 -0
  28. checkpoint-6000/optimizer.bin +3 -0
  29. checkpoint-6000/pytorch_lora_weights.safetensors +3 -0
  30. checkpoint-6000/random_states_0.pkl +3 -0
  31. checkpoint-6000/scheduler.bin +3 -0
  32. checkpoint-8000/model.safetensors +3 -0
  33. checkpoint-8000/optimizer.bin +3 -0
  34. checkpoint-8000/pytorch_lora_weights.safetensors +3 -0
  35. checkpoint-8000/random_states_0.pkl +3 -0
  36. checkpoint-8000/scheduler.bin +3 -0
  37. image_0.png +0 -0
  38. image_1.png +0 -0
  39. image_2.png +0 -0
  40. image_3.png +0 -0
  41. pytorch_lora_weights.safetensors +3 -0
README.md ADDED
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+ ---
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+ base_model: runwayml/stable-diffusion-v1-5
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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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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+ - diffusers-training
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+ - lora
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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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+ # LoRA text2image fine-tuning - A7MED24/DM_lora_zer0p_unet_binary_class_labels
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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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+
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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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