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End of training

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  1. README.md +62 -0
  2. checkpoint-100/optimizer.bin +3 -0
  3. checkpoint-100/pytorch_lora_weights.safetensors +3 -0
  4. checkpoint-100/random_states_0.pkl +3 -0
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  14. checkpoint-400/optimizer.bin +3 -0
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  22. checkpoint-600/optimizer.bin +3 -0
  23. checkpoint-600/pytorch_lora_weights.safetensors +3 -0
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  26. checkpoint-700/optimizer.bin +3 -0
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  30. checkpoint-800/optimizer.bin +3 -0
  31. checkpoint-800/pytorch_lora_weights.safetensors +3 -0
  32. checkpoint-800/random_states_0.pkl +3 -0
  33. checkpoint-800/scheduler.bin +3 -0
  34. checkpoint-900/optimizer.bin +3 -0
  35. checkpoint-900/pytorch_lora_weights.safetensors +3 -0
  36. checkpoint-900/random_states_0.pkl +3 -0
  37. checkpoint-900/scheduler.bin +3 -0
  38. pytorch_lora_weights.safetensors +3 -0
README.md ADDED
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+ ---
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+ base_model: stabilityai/stable-diffusion-xl-base-1.0
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+ library_name: diffusers
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+ license: openrail++
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+ tags:
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+ - text-to-image
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+ - text-to-image
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+ - diffusers-training
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+ - diffusers
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+ - lora
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+ - template:sd-lora
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+ - stable-diffusion-xl
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+ - stable-diffusion-xl-diffusers
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+ instance_prompt: asa
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+ widget: []
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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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+ # SDXL LoRA DreamBooth - reeen115/bolt_sdxl_900
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+
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+ <Gallery />
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+
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+ ## Model description
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+
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+ These are reeen115/bolt_sdxl_900 LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.
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+
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+ The weights were trained using [DreamBooth](https://dreambooth.github.io/).
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+
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+ LoRA for the text encoder was enabled: False.
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+
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+ Special VAE used for training: None.
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+
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+ ## Trigger words
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+
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+ You should use asa to trigger the image generation.
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+
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+ ## Download model
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+
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+ Weights for this model are available in Safetensors format.
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+
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+ [Download](reeen115/bolt_sdxl_900/tree/main) them in the Files & versions tab.
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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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