End of training
Browse files- README.md +25 -0
- checkpoint-500/optimizer.bin +3 -0
- checkpoint-500/pytorch_lora_weights.safetensors +3 -0
- checkpoint-500/random_states_0.pkl +3 -0
- checkpoint-500/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/1707158182.6857944/events.out.tfevents.1707158182.ai1.4080.1 +3 -0
- logs/dreambooth-lora/1707158182.7541358/hparams.yml +56 -0
- logs/dreambooth-lora/events.out.tfevents.1707158182.ai1.4080.0 +3 -0
- pytorch_lora_weights.safetensors +3 -0
README.md
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---
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license: creativeml-openrail-m
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base_model: CompVis/stable-diffusion-v1-4
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instance_prompt: a photo of sks teddybear
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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- text-to-image
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- diffusers
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- lora
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inference: true
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---
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# LoRA DreamBooth - danaleee/teddybear
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These are LoRA adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on a photo of sks teddybear using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following.
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LoRA for the text encoder was enabled: False.
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checkpoint-500/optimizer.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:81c5f7e41d67a2ceb8ae4b058daeba6175567f7824e78d79daf0ff8b0eaa3adf
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size 6592122
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checkpoint-500/pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc51dcd8d34ef227af11dd1c6d9572553d6abd4aa515a917ad9f16f18b9e80ac
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size 3226184
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checkpoint-500/random_states_0.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:c042d37f3720ec0bc4923417d6a7d301372b6c0a09f33546792a8383a47dc246
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size 16036
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checkpoint-500/scheduler.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5a14cab18e3cf6bf4020ba19261b57bd47f02eb286b8412b0d80f0e1c055663a
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size 1000
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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/1707158182.6857944/events.out.tfevents.1707158182.ai1.4080.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:2bcc86be0e3efa461af38fb08b9cb1d53ba8032888f836acc6e690db65bb9ce4
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size 2731
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logs/dreambooth-lora/1707158182.7541358/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: 500
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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: /d1/daeun/custom-diffusion/data/teddybear/
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instance_prompt: a photo of sks teddybear
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learning_rate: 0.0001
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local_rank: 0
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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: 500
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mixed_precision: null
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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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output_dir: /d1/daeun/diffusers/examples/dreambooth/exp/teddybear/
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pre_compute_text_embeddings: false
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pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
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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: 512
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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: false
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use_8bit_adam: false
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validation_epochs: 50
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validation_prompt: A photo of sks teddybear in a bucket
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variant: null
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with_prior_preservation: false
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logs/dreambooth-lora/events.out.tfevents.1707158182.ai1.4080.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:8186563626414f2fe13da7ce5f7ee2ea72e89cfc961c500f4588e8634db3a5a3
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size 10870860
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pytorch_lora_weights.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc51dcd8d34ef227af11dd1c6d9572553d6abd4aa515a917ad9f16f18b9e80ac
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size 3226184
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