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Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
custom-diffusion
Inference Endpoints
Model card Files Metrics Community
briannlongzhao commited on
Commit
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End of training

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Files changed (13) hide show
  1. README.md +3 -8
  2. learned_embeds.safetensors +1 -1
  3. logs/textual_inversion/1706461782.8189495/events.out.tfevents.1706461783.node-0.2803.1 +3 -0
  4. logs/textual_inversion/1706461783.7503953/hparams.yml +50 -0
  5. logs/textual_inversion/1706473860.0429978/events.out.tfevents.1706473861.node-0.2947.1 +3 -0
  6. logs/textual_inversion/1706473863.893395/hparams.yml +50 -0
  7. logs/textual_inversion/events.out.tfevents.1706461782.node-0.2803.0 +3 -0
  8. logs/textual_inversion/events.out.tfevents.1706473858.node-0.2947.0 +3 -0
  9. text_encoder/config.json +2 -2
  10. text_encoder/model.safetensors +2 -2
  11. unet/diffusion_pytorch_model.safetensors +2 -2
  12. vae/config.json +1 -1
  13. vae/diffusion_pytorch_model.safetensors +2 -2
README.md CHANGED
@@ -2,21 +2,16 @@
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  ---
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  license: creativeml-openrail-m
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  base_model: stabilityai/stable-diffusion-2-1
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- instance_prompt: a photo of <new1> modem
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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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- # Custom Diffusion - briannlongzhao/67
 
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- These are Custom Diffusion adaption weights for stabilityai/stable-diffusion-2-1. The weights were trained on a photo of <new1> modem 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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  ---
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  license: creativeml-openrail-m
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  base_model: stabilityai/stable-diffusion-2-1
 
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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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+ - textual_inversion
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  inference: true
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  ---
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+ # Textual inversion text2image fine-tuning - briannlongzhao/67
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+ These are textual inversion adaption weights for stabilityai/stable-diffusion-2-1. 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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+ 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_name: modem
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+ dataloader_num_workers: 0
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+ enable_xformers_memory_efficient_attention: true
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: false
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+ hub_model_id: null
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+ idx: 67
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+ initializer_token: modem
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+ learnable_property: object
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+ learning_rate: 0.008
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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_scheduler: constant
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+ lr_warmup_steps: 0
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+ max_train_steps: 35
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+ mixed_precision: fp16
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+ no_safe_serialization: false
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+ num_train_epochs: 5
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+ num_validation_images: 4
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+ num_vectors: 1
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+ output_dir: /mnt/default/textual_inversion_models_medium/67
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+ placeholder_token: <modem>
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+ pretrained_model_name_or_path: stabilityai/stable-diffusion-2-1
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+ push_to_hub: true
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+ repeats: 1
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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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+ save_as_full_pipeline: false
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+ save_steps: 500
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+ scale_lr: true
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+ seed: null
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+ tokenizer_name: null
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+ train_batch_size: 4
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+ train_data_dir: /mnt/default/imagenet/images/train_medium/n03777754
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+ validation_epochs: null
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+ validation_prompt: null
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+ validation_steps: 100
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+ wnid: n03777754
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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_name: modem
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+ dataloader_num_workers: 0
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+ enable_xformers_memory_efficient_attention: true
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+ gradient_accumulation_steps: 4
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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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+ idx: 67
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+ initializer_token: modem
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+ learnable_property: object
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+ learning_rate: 0.008
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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_scheduler: constant
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+ lr_warmup_steps: 0
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+ max_train_steps: 35
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+ mixed_precision: fp16
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+ no_safe_serialization: false
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+ num_train_epochs: 5
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+ num_validation_images: 4
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+ num_vectors: 1
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+ output_dir: /mnt/default/textual_inversion_models_medium/67
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+ placeholder_token: <modem>
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+ pretrained_model_name_or_path: stabilityai/stable-diffusion-2-1
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+ push_to_hub: true
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+ repeats: 1
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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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+ save_as_full_pipeline: false
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+ save_steps: 500
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+ scale_lr: true
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+ train_batch_size: 4
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