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SidXXD
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path-to-save-model-dog

Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
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SidXXD commited on
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End of training

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Files changed (12) hide show
  1. <new-dog>.bin +3 -0
  2. README.md +22 -0
  3. checkpoint-250/custom_checkpoint_0.pkl +3 -0
  4. checkpoint-250/optimizer.bin +3 -0
  5. checkpoint-250/pytorch_model.bin +3 -0
  6. checkpoint-250/pytorch_model_1.bin +3 -0
  7. checkpoint-250/random_states_0.pkl +3 -0
  8. checkpoint-250/scheduler.bin +3 -0
  9. logs/custom-diffusion/1701352657.104159/events.out.tfevents.1701352657.cudahpc06.2058259.1 +3 -0
  10. logs/custom-diffusion/1701352657.1058373/hparams.yml +57 -0
  11. logs/custom-diffusion/events.out.tfevents.1701352657.cudahpc06.2058259.0 +3 -0
  12. pytorch_custom_diffusion_weights.bin +3 -0
<new-dog>.bin ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:f043b08da3c0afcfd5cf8e2606aacd320552d58954f4f50ec53a3ced6aa15049
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+ size 151785201
README.md ADDED
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+
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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: photo of a <new-dog> dog
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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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+ - custom-diffusion
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+ inference: true
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+ ---
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+
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+ # Custom Diffusion - SidXXD/path-to-save-model-dog
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+
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+ These are Custom Diffusion adaption weights for CompVis/stable-diffusion-v1-4. The weights were trained on photo of a <new-dog> dog using [Custom Diffusion](https://www.cs.cmu.edu/~custom-diffusion). You can find some example images in the following.
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+
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+
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+
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+ For more details on the training, please follow [this link](https://github.com/huggingface/diffusers/blob/main/examples/custom_diffusion).
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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: 250
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+ checkpoints_total_limit: null
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+ class_data_dir: ./real_reg/samples_dog/
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+ class_prompt: dog
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+ concepts_list: null
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+ dataloader_num_workers: 2
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+ enable_xformers_memory_efficient_attention: false
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+ freeze_model: crossattn_kv
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+ gradient_accumulation_steps: 1
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+ gradient_checkpointing: false
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+ hflip: true
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+ hub_model_id: null
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+ hub_token: null
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+ initializer_token: ktn+pll+ucd
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+ instance_data_dir: /home/xide/miniconda3/code/data/CustomDiffusion/data/dog/
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+ instance_prompt: photo of a <new-dog> dog
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+ learning_rate: 1.0e-05
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+ local_rank: -1
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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: 250
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+ mixed_precision: null
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+ modifier_token: <new-dog>
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+ no_safe_serialization: true
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+ noaug: false
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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: path-to-save-model-dog
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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: 0.0
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+ push_to_hub: true
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+ real_prior: false
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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: true
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+ seed: 42
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+ set_grads_to_none: false
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+ tokenizer_name: null
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+ train_batch_size: 2
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+ use_8bit_adam: false
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+ validation_prompt: null
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+ validation_steps: 50
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+ variant: null
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+ with_prior_preservation: false
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