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app.py
CHANGED
@@ -21,15 +21,6 @@ from uploader import upload
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TITLE = '# LoRA + StableDiffusion Training UI'
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DESCRIPTION = 'This is an unofficial demo for [https://github.com/cloneofsimo/lora](https://github.com/cloneofsimo/lora).'
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USAGE_INFO = '''You can train and download models in the "Training" tab, and test them in the "Test" tab.
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You can also test the pretrained models in the [original repo](https://github.com/cloneofsimo/lora).
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Models with names starting with "lora/" are the pretrained models and the ones with names starting with "results/" are your trained models.
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After training, you can press "Reload Weight List" button to load your trained model names.
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Note that your trained models will be deleted when the second training is started.
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'''
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ORIGINAL_SPACE_ID = 'hysts/LoRA-SD-training'
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SPACE_ID = os.getenv('SPACE_ID', ORIGINAL_SPACE_ID)
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SHARED_UI_WARNING = f'''# Attention - This Space doesn't work in this shared UI. You can duplicate and use it with a paid private T4 GPU.
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@@ -103,6 +94,7 @@ def create_training_demo(trainer: Trainer,
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gr.Markdown('''
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- It will take about 8 minutes to train for 1000 steps with a T4 GPU.
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- You may want to try a small number of steps first, like 1, to see if everything works fine in your environment.
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''')
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run_button = gr.Button('Start Training')
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@@ -204,6 +196,8 @@ def create_inference_demo(pipe: InferencePipeline) -> gr.Blocks:
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run_button = gr.Button('Generate')
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gr.Markdown('''
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- The pretrained models for "disney", "illust" and "pop" are trained with the concept prompt "style of sks".
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- The pretrained model for "kiriko" is trained with the concept prompt "game character bnha". For this model, the text encoder is also trained.
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''')
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@@ -283,7 +277,4 @@ with gr.Blocks(css='style.css') as demo:
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with gr.TabItem('Upload'):
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create_upload_demo()
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with gr.Accordion('Usage', open=False):
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gr.Markdown(USAGE_INFO)
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demo.queue(default_enabled=False).launch(share=False)
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TITLE = '# LoRA + StableDiffusion Training UI'
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DESCRIPTION = 'This is an unofficial demo for [https://github.com/cloneofsimo/lora](https://github.com/cloneofsimo/lora).'
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ORIGINAL_SPACE_ID = 'hysts/LoRA-SD-training'
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SPACE_ID = os.getenv('SPACE_ID', ORIGINAL_SPACE_ID)
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SHARED_UI_WARNING = f'''# Attention - This Space doesn't work in this shared UI. You can duplicate and use it with a paid private T4 GPU.
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gr.Markdown('''
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- It will take about 8 minutes to train for 1000 steps with a T4 GPU.
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- You may want to try a small number of steps first, like 1, to see if everything works fine in your environment.
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- Note that your trained models will be deleted when the second training is started. You can upload your trained model in the "Upload" tab.
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''')
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run_button = gr.Button('Start Training')
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run_button = gr.Button('Generate')
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gr.Markdown('''
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- Models with names starting with "lora/" are the pretrained models provided in the [original repo](https://github.com/cloneofsimo/lora), and the ones with names starting with "results/" are your trained models.
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- After training, you can press "Reload Weight List" button to load your trained model names.
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- The pretrained models for "disney", "illust" and "pop" are trained with the concept prompt "style of sks".
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- The pretrained model for "kiriko" is trained with the concept prompt "game character bnha". For this model, the text encoder is also trained.
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''')
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with gr.TabItem('Upload'):
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create_upload_demo()
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demo.queue(default_enabled=False).launch(share=False)
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