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End of training

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  1. .gitattributes +4 -0
  2. README.md +74 -0
  3. image_0.png +3 -0
  4. image_1.png +3 -0
  5. image_2.png +3 -0
  6. image_3.png +3 -0
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  31. pytorch_lora_weights.safetensors +3 -0
.gitattributes CHANGED
@@ -33,3 +33,7 @@ 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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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: a photo of wjz person
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+ widget:
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+ - text: A photo of wjz person in jungle
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+ output:
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+ url: image_0.png
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+ - text: A photo of wjz person in jungle
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+ output:
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+ url: image_1.png
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+ - text: A photo of wjz person in jungle
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+ output:
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+ url: image_2.png
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+ - text: A photo of wjz person in jungle
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+ output:
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+ url: image_3.png
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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 - farazfo/sara2-xl-text-encoder
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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 farazfo/sara2-xl-text-encoder 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: True.
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+
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+ Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
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+
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+ ## Trigger words
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+
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+ You should use a photo of wjz person 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](farazfo/sara2-xl-text-encoder/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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+ adam_beta1: 0.9
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+ instance_data_dir: sara1
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+ local_rank: -1
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+ logging_dir: logs
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+ lr_num_cycles: 1
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+ lr_scheduler: constant
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+ mixed_precision: bf16
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+ num_class_images: 100
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+ num_train_epochs: 500
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+ num_validation_images: 4
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+ optimizer: AdamW
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+ output_dir: sara2-xl-text-encoder
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+ output_kohya_format: false
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+ pretrained_model_name_or_path: stabilityai/stable-diffusion-xl-base-1.0
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