mirror of
https://github.com/vladmandic/automatic
synced 2026-09-19 09:14:35 +02:00
fix new k-diffusers
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@@ -144,7 +144,7 @@ def create_ui():
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model_checkhash_btn.click(fn=sd_models.update_model_hashes, inputs=[], outputs=[models_outcome])
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with gr.Row():
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model_table = gr.DataFrame(
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value = model_data,
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value = None,
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headers = model_headers,
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label = 'Model data',
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show_label = True,
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@@ -209,6 +209,7 @@ def create_ui():
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return f'Diffuser model downloaded: model="{hub_id}"'
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with gr.Column(scale=6):
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gr.HTML('<h2>Search for models</h2>Select a model from the search results to download<br><br>')
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with gr.Row():
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hf_search_text = gr.Textbox('', label = 'Search models', placeholder='search huggingface models')
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hf_search_btn = ToolButton(value="🔍", label="Search")
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@@ -224,12 +225,13 @@ def create_ui():
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hf_token = gr.Textbox('', label = 'Huggingface token', placeholder='optional access token for private or gated models')
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hf_mirror = gr.Textbox('', label = 'Huggingface mirror', placeholder='optional mirror site for downloads')
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with gr.Column(scale=1):
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gr.HTML('<br>')
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hf_download_model_btn = gr.Button(value="Download model", variant='primary')
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with gr.Row():
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hf_headers = ['Name', 'Pipeline', 'Tags', 'Downloads', 'Updated', 'URL']
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hf_types = ['str', 'str', 'str', 'number', 'date', 'markdown']
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hf_results = gr.DataFrame([], label = 'Search results', show_label = True, interactive = False, wrap = True, overflow_row_behaviour = 'paginate', max_rows = 10, headers = hf_headers, datatype = hf_types, type='array')
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hf_results = gr.DataFrame(None, label = 'Search results', show_label = True, interactive = False, wrap = True, overflow_row_behaviour = 'paginate', max_rows = 10, headers = hf_headers, datatype = hf_types, type='array')
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hf_search_text.submit(fn=hf_search, inputs=[hf_search_text], outputs=[hf_results])
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hf_search_btn.click(fn=hf_search, inputs=[hf_search_text], outputs=[hf_results])
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@@ -377,7 +379,7 @@ def create_ui():
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civit_previews_rehash = gr.Checkbox(value=True, label="Check alternative hash")
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with gr.Row(style={'margin-top': '1em'}):
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gr.HTML('<h2>Search for models</h2>')
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gr.HTML('<h2>Search for models</h2>Select a model, model version and and model variant from the search results to download<br>')
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with gr.Row():
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with gr.Column(scale=1):
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civit_model_type = gr.Dropdown(label='Model type', choices=['SD 1.5', 'SD XL', 'LoRA', 'Other'], value='LoRA')
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