codyreading
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End of training
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- <new1>.bin +1 -1
- <new2>.bin +1 -1
- README.md +2 -2
- checkpoint-1000/custom_checkpoint_0.pkl +3 -0
- checkpoint-1000/optimizer.bin +3 -0
- checkpoint-1000/pytorch_model.bin +3 -0
- checkpoint-1000/pytorch_model_1.bin +3 -0
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- checkpoint-1000/scheduler.bin +3 -0
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README.md
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---
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license: creativeml-openrail-m
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base_model:
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instance_prompt: None
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tags:
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- stable-diffusion
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# Custom Diffusion - codyreading/custom_diffusion
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These are Custom Diffusion adaption weights for
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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: None
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tags:
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- stable-diffusion
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# Custom Diffusion - codyreading/custom_diffusion
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These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on None using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following.
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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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freeze_model: crossattn
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learning_rate: 5.0e-06
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logging_dir: logs
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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: 1000
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mixed_precision: null
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modifier_token: <new1>+<new2>
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no_safe_serialization: false
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noaug: true
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num_class_images: 200
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num_train_epochs: 1
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num_validation_images: 2
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output_dir: /home/cra80/Checkpoints/custom_diffusion
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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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real_prior: true
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report_to: tensorboard
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resolution: 512
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revision: null
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sample_batch_size: 4
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validation_steps: 50
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with_prior_preservation: true
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