taki0112 commited on
Commit
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1 Parent(s): 5b75260

End of training

Browse files
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README.md ADDED
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+
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+ ---
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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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+ - lora
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+ - template:sd-lora
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+ widget:
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+
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+ - text: 'a fish in sks style'
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+ output:
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+ url:
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+ "image_0.png"
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+
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+ - text: 'a fish in sks style'
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+ output:
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+ url:
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+ "image_1.png"
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+
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+ - text: 'a fish in sks style'
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+ output:
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+ url:
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+ "image_2.png"
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+
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+ - text: 'a fish in sks style'
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+ output:
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+ url:
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+ "image_3.png"
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+
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+ base_model: stabilityai/stable-diffusion-xl-base-1.0
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+ instance_prompt: a village in sks style
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+ license: openrail++
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+ ---
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+
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+ # SDXL LoRA DreamBooth - taki0112/lora-trained-xl_vangogh_split
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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 taki0112/lora-trained-xl_vangogh_split 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: 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 village in sks style 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](taki0112/lora-trained-xl_vangogh_split/tree/main) them in the Files & versions tab.
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+
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+ adam_beta1: 0.9
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+ adam_beta2: 0.999
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+ adam_epsilon: 1.0e-08
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+ adam_weight_decay: 0.0001
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+ adam_weight_decay_text_encoder: 0.001
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+ mixed_precision: fp16
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+ num_class_images: 100
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+ num_train_epochs: 250
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+ num_validation_images: 4
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+ optimizer: AdamW
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+ output_dir: lora-trained-xl_vangogh_split
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+ pretrained_model_name_or_path: stabilityai/stable-diffusion-xl-base-1.0
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+ pretrained_vae_model_name_or_path: madebyollin/sdxl-vae-fp16-fix
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+ resolution: 512
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+ sample_batch_size: 4
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+ scale_lr: false
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+ text_encoder_lr: 5.0e-06
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+ train_batch_size: 1
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+ train_text_encoder: false
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+ use_8bit_adam: false
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+ validation_epochs: 25
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+ validation_prompt: a fish in sks style
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+ num_validation_images: 4
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+ optimizer: AdamW
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+ output_dir: lora-trained-xl_vangogh_split
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