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SD-Dog-Test4

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End of training

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  1. README.md +26 -0
  2. SD-Dog-Test4.log +37 -0
  3. checkpoint-10/optimizer.bin +3 -0
  4. checkpoint-10/pytorch_lora_weights.safetensors +3 -0
  5. checkpoint-10/random_states_0.pkl +3 -0
  6. checkpoint-10/scheduler.bin +3 -0
  7. checkpoint-5/optimizer.bin +3 -0
  8. checkpoint-5/pytorch_lora_weights.safetensors +3 -0
  9. checkpoint-5/random_states_0.pkl +3 -0
  10. checkpoint-5/scheduler.bin +3 -0
  11. image_0.png +0 -0
  12. image_1.png +0 -0
  13. image_2.png +0 -0
  14. image_3.png +0 -0
  15. pytorch_lora_weights.safetensors +3 -0
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: runwayml/stable-diffusion-v1-5
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+ instance_prompt: a photo of sks 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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+ - lora
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+ inference: true
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+ ---
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+
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+ # LoRA DreamBooth - zeerakwyne/SD-Dog-Test4
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+
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+ These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were trained on a photo of sks dog using [DreamBooth](https://dreambooth.github.io/). 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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+ LoRA for the text encoder was enabled: False.
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+
SD-Dog-Test4.log ADDED
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+ 10/15/2023 00:01:15 - INFO - app - Distributed environment: NO
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+ Num processes: 1
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+ Process index: 0
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+ Local process index: 0
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+ Device: cuda
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+
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+ Mixed precision type: no
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+
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+ 10/15/2023 00:01:21 - INFO - app - Num examples = 5
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+ 10/15/2023 00:01:21 - INFO - app - Num batches each epoch = 5
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+ 10/15/2023 00:01:21 - INFO - app - Num Epochs = 2
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+ 10/15/2023 00:01:21 - INFO - app - Instantaneous batch size per device = 1
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+ 10/15/2023 00:01:21 - INFO - app - Total train batch size (w. parallel, distributed & accumulation) = 1
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+ 10/15/2023 00:01:21 - INFO - app - Gradient Accumulation steps = 1
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+ 10/15/2023 00:01:21 - INFO - app - Training Steps = 10
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+ 10/15/2023 00:01:21 - INFO - app - STEP = 1
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+ 10/15/2023 00:01:29 - INFO - app - STEP = 2
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+ 10/15/2023 00:01:36 - INFO - app - STEP = 3
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+ 10/15/2023 00:01:42 - INFO - app - STEP = 4
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+ 10/15/2023 00:01:49 - INFO - app - STEP = 5
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+ 10/15/2023 00:01:55 - INFO - accelerate.accelerator - Saving current state to models/SD-Dog-Test4/checkpoint-5
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+ 10/15/2023 00:01:55 - INFO - accelerate.checkpointing - Optimizer state saved in models/SD-Dog-Test4/checkpoint-5/optimizer.bin
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+ 10/15/2023 00:01:55 - INFO - accelerate.checkpointing - Scheduler state saved in models/SD-Dog-Test4/checkpoint-5/scheduler.bin
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+ 10/15/2023 00:01:55 - INFO - accelerate.checkpointing - Random states saved in models/SD-Dog-Test4/checkpoint-5/random_states_0.pkl
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+ 10/15/2023 00:01:55 - INFO - app - Saved state to models/SD-Dog-Test4/checkpoint-5
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+ 10/15/2023 00:01:55 - INFO - app - Running validation...
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+ Generating 4 images with prompt: A photo of sks dog in a bucket.
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+ 10/15/2023 00:02:21 - INFO - app - STEP = 6
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+ 10/15/2023 00:02:28 - INFO - app - STEP = 7
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+ 10/15/2023 00:02:34 - INFO - app - STEP = 8
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+ 10/15/2023 00:02:41 - INFO - app - STEP = 9
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+ 10/15/2023 00:02:48 - INFO - app - STEP = 10
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+ 10/15/2023 00:02:54 - INFO - accelerate.accelerator - Saving current state to models/SD-Dog-Test4/checkpoint-10
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+ 10/15/2023 00:02:54 - INFO - accelerate.checkpointing - Optimizer state saved in models/SD-Dog-Test4/checkpoint-10/optimizer.bin
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+ 10/15/2023 00:02:54 - INFO - accelerate.checkpointing - Scheduler state saved in models/SD-Dog-Test4/checkpoint-10/scheduler.bin
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+ 10/15/2023 00:02:54 - INFO - accelerate.checkpointing - Random states saved in models/SD-Dog-Test4/checkpoint-10/random_states_0.pkl
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+ 10/15/2023 00:02:54 - INFO - app - Saved state to models/SD-Dog-Test4/checkpoint-10
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