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jqlive
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sd15-digital-oil-arcane

Text-to-Image
Diffusers
TensorBoard
stable-diffusion
stable-diffusion-diffusers
diffusers-training
lora
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  1. README.md +43 -0
  2. image_0.png +0 -0
  3. image_1.png +0 -0
  4. image_2.png +0 -0
  5. image_3.png +0 -0
  6. logs/text2image-fine-tune/1719475547.4632971/events.out.tfevents.1719475547.DESKTOP-S8JBNEE.216027.1 +3 -0
  7. logs/text2image-fine-tune/1719475547.4641712/hparams.yml +50 -0
  8. logs/text2image-fine-tune/1719475744.2250109/events.out.tfevents.1719475744.DESKTOP-S8JBNEE.217722.1 +3 -0
  9. logs/text2image-fine-tune/1719475744.2267156/hparams.yml +50 -0
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  14. logs/text2image-fine-tune/events.out.tfevents.1719475779.DESKTOP-S8JBNEE.218308.0 +3 -0
  15. pytorch_lora_weights.safetensors +3 -0
README.md ADDED
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+ ---
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+ base_model: runwayml/stable-diffusion-v1-5
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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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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+ - diffusers-training
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+ - lora
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+ inference: true
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+ ---
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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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+
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+
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+ # LoRA text2image fine-tuning - jqlive/sd15-digital-oil-arcane
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+ These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the jqlive/digital_oil dataset. You can find some example images in the following.
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+
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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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+
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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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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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
image_0.png ADDED
image_1.png ADDED
image_2.png ADDED
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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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+ cache_dir: null
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+ caption_column: caption
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+ center_crop: true
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+ checkpointing_steps: 500
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+ checkpoints_total_limit: null
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+ dataloader_num_workers: 8
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+ dataset_config_name: null
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+ dataset_name: jqlive/digital_oil
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+ enable_xformers_memory_efficient_attention: false
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: false
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+ hub_model_id: sd15-digital-oil-arcane
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+ hub_token: null
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+ image_column: image
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+ learning_rate: 0.0001
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+ local_rank: -1
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+ logging_dir: logs
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+ lr_scheduler: cosine
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+ lr_warmup_steps: 0
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+ max_grad_norm: 1.0
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+ max_train_samples: null
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+ max_train_steps: 15000
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+ mixed_precision: null
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+ noise_offset: 0
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+ num_train_epochs: 518
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+ num_validation_images: 4
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+ output_dir: /home/remko2/developer/dreambooth/trained_models/digital_oil
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+ prediction_type: null
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+ pretrained_model_name_or_path: runwayml/stable-diffusion-v1-5
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+ push_to_hub: true
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+ random_flip: 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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+ scale_lr: false
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+ seed: 1337
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+ snr_gamma: null
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+ train_batch_size: 1
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+ train_data_dir: null
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+ use_8bit_adam: false
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+ validation_epochs: 1
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+ validation_prompt: Totoro
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+ variant: null
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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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+ checkpointing_steps: 500
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+ dataset_config_name: null
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+ dataset_name: jqlive/digital_oil
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+ enable_xformers_memory_efficient_attention: false
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+ gradient_checkpointing: false
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+ hub_model_id: sd15-digital-oil-arcane
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+ hub_token: null
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+ image_column: image
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+ learning_rate: 0.0001
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+ local_rank: -1
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+ logging_dir: logs
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+ lr_scheduler: cosine
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+ lr_warmup_steps: 0
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+ max_grad_norm: 1.0
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+ max_train_samples: null
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+ max_train_steps: 15000
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+ mixed_precision: null
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+ noise_offset: 0
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+ num_validation_images: 4
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+ output_dir: /home/remko2/developer/dreambooth/trained_models/digital_oil
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+ prediction_type: null
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