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Upload app.py
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app.py
CHANGED
@@ -87,11 +87,12 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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# raise gr.Error("You must select a LoRA before proceeding.")
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progress(0, desc="Preparing Inference.")
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if is_valid_lora(lora_json):
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with calculateDuration("Loading LoRA weights"):
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fuse_loras(pipe, lora_json)
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trigger_word = get_trigger_word(lora_json)
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-
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selected_lora = loras[selected_index]
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lora_path = selected_lora["repo"]
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trigger_word = selected_lora["trigger_word"]
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@@ -101,7 +102,6 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
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else:
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pipe.load_lora_weights(lora_path)
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else: trigger_word = ""
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# Set random seed for reproducibility
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with calculateDuration("Randomizing seed"):
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@@ -251,8 +251,8 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
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gr.on(
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triggers=[lora_download.click, lora_download_url.submit],
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fn=download_my_lora,
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inputs=[lora_download_url, lora_repo[lambda i:
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outputs=[lora_repo[lambda i:
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scroll_to_output=True,
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queue=True,
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show_api=False,
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# raise gr.Error("You must select a LoRA before proceeding.")
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progress(0, desc="Preparing Inference.")
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trigger_word = ""
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if is_valid_lora(lora_json):
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with calculateDuration("Loading LoRA weights"):
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fuse_loras(pipe, lora_json)
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trigger_word = get_trigger_word(lora_json)
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if selected_index is not None:
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selected_lora = loras[selected_index]
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lora_path = selected_lora["repo"]
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trigger_word = selected_lora["trigger_word"]
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pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
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else:
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pipe.load_lora_weights(lora_path)
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# Set random seed for reproducibility
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with calculateDuration("Randomizing seed"):
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gr.on(
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triggers=[lora_download.click, lora_download_url.submit],
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fn=download_my_lora,
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inputs=[lora_download_url, lora_repo[int(lambda i: i - 1, lora_slot)]],
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outputs=[lora_repo[int(lambda i: i - 1, lora_slot)]],
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scroll_to_output=True,
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queue=True,
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show_api=False,
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