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Model card auto-generated by SimpleTuner

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  1. README.md +5 -5
README.md CHANGED
@@ -16,7 +16,7 @@ widget:
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  negative_prompt: 'blurry, cropped, ugly'
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  output:
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  url: ./assets/image_0_0.png
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- - text: 'a photo of bartus'
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  parameters:
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  negative_prompt: 'blurry, cropped, ugly'
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  output:
@@ -33,7 +33,7 @@ The main validation prompt used during training was:
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  ```
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- a photo of bartus
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  ```
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  ## Validation settings
@@ -57,8 +57,8 @@ You may reuse the base model text encoder for inference.
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  ## Training settings
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- - Training epochs: 23
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- - Training steps: 600
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  - Learning rate: 0.0001
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  - Effective batch size: 1
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  - Micro-batch size: 1
@@ -121,7 +121,7 @@ lora_scale = 1.0
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  wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
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  wrapper.merge_to()
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- prompt = "a photo of bartus"
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  pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
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  image = pipeline(
 
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  negative_prompt: 'blurry, cropped, ugly'
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  output:
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  url: ./assets/image_0_0.png
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+ - text: 'a photo of man bartus'
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  parameters:
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  negative_prompt: 'blurry, cropped, ugly'
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  output:
 
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  ```
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+ a photo of man bartus
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  ```
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  ## Validation settings
 
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  ## Training settings
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+ - Training epochs: 35
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+ - Training steps: 900
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  - Learning rate: 0.0001
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  - Effective batch size: 1
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  - Micro-batch size: 1
 
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  wrapper, _ = create_lycoris_from_weights(lora_scale, adapter_id, pipeline.transformer)
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  wrapper.merge_to()
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+ prompt = "a photo of man bartus"
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  pipeline.to('cuda' if torch.cuda.is_available() else 'mps' if torch.backends.mps.is_available() else 'cpu')
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  image = pipeline(