End of training
Browse files- README.md +47 -0
- checkpoint-10000/optimizer.bin +3 -0
- checkpoint-10000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-10000/random_states_0.pkl +3 -0
- checkpoint-10000/scheduler.bin +3 -0
- checkpoint-20000/optimizer.bin +3 -0
- checkpoint-20000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-20000/random_states_0.pkl +3 -0
- checkpoint-20000/scheduler.bin +3 -0
- checkpoint-30000/optimizer.bin +3 -0
- checkpoint-30000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-30000/random_states_0.pkl +3 -0
- checkpoint-30000/scheduler.bin +3 -0
- checkpoint-40000/optimizer.bin +3 -0
- checkpoint-40000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-40000/random_states_0.pkl +3 -0
- checkpoint-40000/scheduler.bin +3 -0
- checkpoint-50000/optimizer.bin +3 -0
- checkpoint-50000/pytorch_lora_weights.safetensors +3 -0
- checkpoint-50000/random_states_0.pkl +3 -0
- checkpoint-50000/scheduler.bin +3 -0
- image_0.png +0 -0
- image_1.png +0 -0
- image_2.png +0 -0
- image_3.png +0 -0
- logs/dreambooth-lora/1731150191.5200737/events.out.tfevents.1731150191.3833958850f8.4728.1 +3 -0
- logs/dreambooth-lora/1731150191.52176/hparams.yml +56 -0
- logs/dreambooth-lora/events.out.tfevents.1731150191.3833958850f8.4728.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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base_model: kyujinpy/KO-stable-diffusion-disney
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library_name: diffusers
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license: creativeml-openrail-m
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tags:
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- text-to-image
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- diffusers
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- lora
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- diffusers-training
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- stable-diffusion
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- stable-diffusion-diffusers
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inference: true
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instance_prompt: 배불러
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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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# LoRA DreamBooth - KHongJae/LoRA_Disney_0to50000
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These are LoRA adaption weights for kyujinpy/KO-stable-diffusion-disney. The weights were trained on 배불러 using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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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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LoRA for the text encoder was enabled: True.
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## Intended uses & limitations
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#### How to use
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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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#### Limitations and bias
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[TODO: provide examples of latent issues and potential remediations]
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## Training details
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[TODO: describe the data used to train the model]
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image_0.png
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image_1.png
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image_2.png
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image_3.png
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logs/dreambooth-lora/1731150191.5200737/events.out.tfevents.1731150191.3833958850f8.4728.1
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logs/dreambooth-lora/1731150191.52176/hparams.yml
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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: 0.01
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allow_tf32: false
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center_crop: false
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checkpointing_steps: 10000
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checkpoints_total_limit: null
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class_data_dir: null
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class_labels_conditioning: null
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class_prompt: null
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dataloader_num_workers: 0
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enable_xformers_memory_efficient_attention: false
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gradient_accumulation_steps: 1
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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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instance_data_dir: /content/full_caption_rmtxt_dataset
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instance_prompt: "\uBC30\uBD88\uB7EC"
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learning_rate: 1.0e-06
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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: 50000
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mixed_precision: 'no'
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num_class_images: 100
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num_train_epochs: 2
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num_validation_images: 4
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output_dir: LoRA_Disney_0to50000
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pre_compute_text_embeddings: false
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pretrained_model_name_or_path: kyujinpy/KO-stable-diffusion-disney
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prior_generation_precision: null
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prior_loss_weight: 1.0
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push_to_hub: true
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rank: 4
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report_to: tensorboard
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resolution: 768
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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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text_encoder_use_attention_mask: false
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tokenizer_max_length: null
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tokenizer_name: null
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train_batch_size: 1
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train_text_encoder: true
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use_8bit_adam: false
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validation_epochs: 1
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validation_prompt: "\uBC30\uBD88\uB7EC"
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variant: null
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with_prior_preservation: false
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