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End of training

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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 sks dog
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+ widget:
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+ - text: photo of sks dog in a bucket
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+ output:
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+ url: image_0.png
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+ - text: photo of sks dog in a bucket
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+ output:
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+ url: image_1.png
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+ - text: photo of sks dog in a bucket
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+ output:
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+ url: image_2.png
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+ - text: photo of sks dog in a bucket
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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 - nikita200/lora-trained-xl-v5
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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 nikita200/lora-trained-xl-v5 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 photo of sks dog 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](nikita200/lora-trained-xl-v5/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]
image_0.png ADDED
image_1.png ADDED
image_2.png ADDED
image_3.png ADDED
logs/dreambooth-lora-sd-xl/1724150291.6230476/events.out.tfevents.1724150291.0151-dsm-prxmx30107.47554.1 ADDED
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logs/dreambooth-lora-sd-xl/1724150291.6252766/hparams.yml ADDED
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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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+ allow_tf32: false
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+ cache_dir: null
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+ caption_column: null
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+ center_crop: false
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+ checkpointing_steps: 500
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+ checkpoints_total_limit: null
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+ class_data_dir: null
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+ class_prompt: null
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+ dataloader_num_workers: 0
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+ dataset_config_name: null
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+ dataset_name: null
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+ do_edm_style_training: false
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+ enable_xformers_memory_efficient_attention: false
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+ gradient_accumulation_steps: 2
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+ gradient_checkpointing: false
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+ hub_model_id: null
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+ hub_token: null
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+ image_column: image
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+ instance_data_dir: dog
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+ instance_prompt: a photo of sks dog
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+ learning_rate: 0.0001
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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_power: 1.0
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+ lr_scheduler: constant
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+ lr_warmup_steps: 0
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+ max_grad_norm: 1.0
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+ max_train_steps: 250
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+ mixed_precision: 'no'
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+ num_class_images: 100
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+ num_train_epochs: 125
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+ num_validation_images: 4
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+ optimizer: AdamW
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+ output_dir: lora-trained-xl-v5
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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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+ pretrained_vae_model_name_or_path: madebyollin/sdxl-vae-fp16-fix
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+ prior_generation_precision: null
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+ prior_loss_weight: 1.0
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+ prodigy_beta3: null
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+ prodigy_decouple: true
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+ prodigy_safeguard_warmup: true
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+ prodigy_use_bias_correction: true
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+ push_to_hub: true
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+ random_flip: false
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+ rank: 4
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+ repeats: 1
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+ report_to: tensorboard
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+ resolution: 128
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+ resume_from_checkpoint: null
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+ revision: null
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+ sample_batch_size: 4
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+ scale_lr: false
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+ seed: 0
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+ snr_gamma: null
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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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+ use_dora: false
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+ validation_epochs: 25
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+ validation_prompt: photo of sks dog in a bucket
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+ variant: null
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+ with_prior_preservation: false
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