Upgrade Gradio
Fix Gradio issues Fix missing LoCon new GUI
This commit is contained in:
bmaltais
parent
482d7834d1
commit
4c762e3abb
@ -355,6 +355,7 @@ def gradio_source_model():
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pretrained_model_name_or_path = gr.Textbox(
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label='Pretrained model name or path',
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placeholder='enter the path to custom model or name of pretrained model',
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value='runwayml/stable-diffusion-v1-5'
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)
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pretrained_model_name_or_path_file = gr.Button(
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document_symbol, elem_id='open_folder_small'
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@ -373,7 +374,7 @@ def gradio_source_model():
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outputs=pretrained_model_name_or_path,
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)
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model_list = gr.Dropdown(
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label='(Optional) Model Quick Pick',
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label='Model Quick Pick',
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choices=[
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'custom',
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'stabilityai/stable-diffusion-2-1-base',
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@ -383,6 +384,7 @@ def gradio_source_model():
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'runwayml/stable-diffusion-v1-5',
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'CompVis/stable-diffusion-v1-4',
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],
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value='runwayml/stable-diffusion-v1-5'
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)
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save_model_as = gr.Dropdown(
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label='Save trained model as',
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@ -397,7 +399,7 @@ def gradio_source_model():
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)
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with gr.Row():
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v2 = gr.Checkbox(label='v2', value=True)
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v2 = gr.Checkbox(label='v2', value=False)
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v_parameterization = gr.Checkbox(
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label='v_parameterization', value=False
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)
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70
lora_gui.py
70
lora_gui.py
@ -123,7 +123,7 @@ def save_configuration(
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caption_dropout_rate,
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optimizer,
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optimizer_args,noise_offset,
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locon=0, conv_dim=0, conv_alpha=0,
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LoRA_type='Standard', conv_dim=0, conv_alpha=0,
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):
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# Get list of function parameters and values
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parameters = list(locals().items())
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@ -231,7 +231,7 @@ def open_configuration(
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caption_dropout_rate,
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optimizer,
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optimizer_args,noise_offset,
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locon=0, conv_dim=0, conv_alpha=0,
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LoRA_type='Standard', conv_dim=0, conv_alpha=0,
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):
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# Get list of function parameters and values
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parameters = list(locals().items())
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@ -256,6 +256,12 @@ def open_configuration(
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if not key in ['file_path']:
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values.append(my_data.get(key, value))
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# This next section is about making the LoCon parameters visible if LoRA_type = 'Standard'
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if my_data.get('LoRA_type', 'Standard') == 'LoCon':
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values.append(gr.Group.update(visible=True))
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else:
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values.append(gr.Group.update(visible=False))
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return tuple(values)
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@ -319,7 +325,7 @@ def train_model(
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caption_dropout_rate,
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optimizer,
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optimizer_args,noise_offset,
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locon, conv_dim, conv_alpha,
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LoRA_type, conv_dim, conv_alpha,
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):
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if pretrained_model_name_or_path == '':
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msgbox('Source model information is missing')
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@ -455,7 +461,7 @@ def train_model(
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run_cmd += f' --save_model_as={save_model_as}'
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if not float(prior_loss_weight) == 1.0:
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run_cmd += f' --prior_loss_weight={prior_loss_weight}'
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if locon:
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if LoRA_type == 'LoCon':
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getlocon(os.path.exists(os.path.join(path_of_this_folder, 'locon')))
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run_cmd += f' --network_module=locon.locon.locon_kohya'
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run_cmd += f' --network_args "conv_dim={conv_dim}" "conv_alpha={conv_alpha}"'
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@ -634,6 +640,14 @@ def lora_tab(
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)
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with gr.Tab('Training parameters'):
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with gr.Row():
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LoRA_type = gr.Dropdown(
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label='LoRA type',
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choices=[
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'Standard',
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'LoCon',
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],
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value='Standard'
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)
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lora_network_weights = gr.Textbox(
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label='LoRA network weights',
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placeholder='{Optional) Path to existing LoRA network weights to resume training',
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@ -666,6 +680,7 @@ def lora_tab(
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lr_scheduler_value='cosine',
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lr_warmup_value='10',
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)
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with gr.Row():
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text_encoder_lr = gr.Textbox(
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label='Text Encoder learning rate',
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@ -693,6 +708,33 @@ def lora_tab(
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step=1,
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interactive=True,
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)
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with gr.Group(visible=False) as LoCon_group:
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def LoRA_type_change(LoRA_type):
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if LoRA_type == "LoCon":
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return gr.Group.update(visible=True)
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else:
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return gr.Group.update(visible=False)
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with gr.Row():
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# locon= gr.Checkbox(label='Train a LoCon instead of a general LoRA (does not support v2 base models) (may not be able to some utilities now)', value=False)
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conv_dim = gr.Slider(
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minimum=1,
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maximum=512,
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value=1,
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step=1,
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label='LoCon Convolution Rank (Dimension)',
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)
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conv_alpha = gr.Slider(
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minimum=1,
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maximum=512,
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value=1,
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step=1,
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label='LoCon Convolution Alpha',
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)
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# Show of hide LoCon conv settings depending on LoRA type selection
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LoRA_type.change(LoRA_type_change, inputs=[LoRA_type], outputs=[LoCon_group])
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with gr.Row():
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max_resolution = gr.Textbox(
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label='Max resolution',
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@ -708,22 +750,6 @@ def lora_tab(
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)
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enable_bucket = gr.Checkbox(label='Enable buckets', value=True)
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with gr.Accordion('Advanced Configuration', open=False):
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with gr.Row():
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locon= gr.Checkbox(label='Train a LoCon instead of a general LoRA (does not support v2 base models) (may not be able to some utilities now)', value=False)
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conv_dim = gr.Slider(
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minimum=1,
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maximum=512,
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value=1,
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step=1,
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label='LoCon Convolution Rank (Dimension)',
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)
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conv_alpha = gr.Slider(
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minimum=1,
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maximum=512,
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value=1,
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step=1,
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label='LoCon Convolution Alpha',
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)
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with gr.Row():
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no_token_padding = gr.Checkbox(
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label='No token padding', value=False
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@ -869,13 +895,13 @@ def lora_tab(
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caption_dropout_rate,
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optimizer,
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optimizer_args,noise_offset,
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locon, conv_dim, conv_alpha,
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LoRA_type, conv_dim, conv_alpha,
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]
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button_open_config.click(
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open_configuration,
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inputs=[config_file_name] + settings_list,
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outputs=[config_file_name] + settings_list,
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outputs=[config_file_name] + settings_list + [LoCon_group],
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)
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button_save_config.click(
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@ -1,28 +1,28 @@
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accelerate==0.15.0
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transformers==4.26.0
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ftfy==6.1.1
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albumentations==1.3.0
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opencv-python==4.7.0.68
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einops==0.6.0
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diffusers[torch]==0.10.2
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pytorch-lightning==1.9.0
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bitsandbytes==0.35.0
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tensorboard==2.10.1
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safetensors==0.2.6
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gradio==3.16.2
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altair==4.2.2
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easygui==0.98.3
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tk==0.1.0
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lion-pytorch==0.0.6
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bitsandbytes==0.35.0
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dadaptation==1.5
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diffusers[torch]==0.10.2
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easygui==0.98.3
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einops==0.6.0
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ftfy==6.1.1
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gradio==3.19.1
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lion-pytorch==0.0.6
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opencv-python==4.7.0.68
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pytorch-lightning==1.9.0
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safetensors==0.2.6
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tensorboard==2.10.1
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tk==0.1.0
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transformers==4.26.0
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# for BLIP captioning
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fairscale==0.4.13
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requests==2.28.2
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timm==0.6.12
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fairscale==0.4.13
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# for WD14 captioning
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# tensorflow<2.11
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tensorflow==2.10.1
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huggingface-hub==0.12.0
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tensorflow==2.10.1
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# xformers @ https://github.com/C43H66N12O12S2/stable-diffusion-webui/releases/download/f/xformers-0.0.14.dev0-cp310-cp310-win_amd64.whl
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# for kohya_ss library
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.
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