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2caf84c
1
Parent(s):
8458096
Add custom LoRA loading
Browse files
app.py
CHANGED
@@ -1,3 +1,4 @@
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import gradio as gr
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import json
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import logging
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@@ -5,6 +6,7 @@ import torch
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from PIL import Image
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import spaces
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from diffusers import DiffusionPipeline
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import copy
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import random
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import time
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@@ -35,7 +37,6 @@ class calculateDuration:
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else:
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print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
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-
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def update_selection(evt: gr.SelectData, width, height):
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selected_lora = loras[evt.index]
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new_placeholder = f"Type a prompt for {selected_lora['title']}"
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@@ -86,9 +87,10 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
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if "weights" in selected_lora:
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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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-
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# Set random seed for reproducibility
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with calculateDuration("Randomizing seed"):
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if randomize_seed:
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@@ -96,9 +98,80 @@ def run_lora(prompt, cfg_scale, steps, selected_index, randomize_seed, seed, wid
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image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
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pipe.to("cpu")
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pipe.unload_lora_weights()
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return image, seed
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run_lora.zerogpu = True
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css = '''
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@@ -107,6 +180,10 @@ css = '''
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#title h1{font-size: 3em; display:inline-flex; align-items:center}
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#title img{width: 100px; margin-right: 0.5em}
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#gallery .grid-wrap{height: 10vh}
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'''
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with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
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title = gr.HTML(
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@@ -129,7 +206,11 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
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columns=3,
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elem_id="gallery"
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)
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-
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with gr.Column(scale=4):
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result = gr.Image(label="Generated Image")
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@@ -154,7 +235,15 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
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inputs=[width, height],
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outputs=[prompt, selected_info, selected_index, width, height]
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)
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-
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gr.on(
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triggers=[generate_button.click, prompt.submit],
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fn=run_lora,
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import os
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import gradio as gr
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import json
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import logging
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from PIL import Image
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import spaces
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from diffusers import DiffusionPipeline
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from huggingface_hub import hf_hub_download, HfFileSystem, ModelCard, snapshot_download
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import copy
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import random
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import time
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else:
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print(f"Elapsed time: {self.elapsed_time:.6f} seconds")
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def update_selection(evt: gr.SelectData, width, height):
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selected_lora = loras[evt.index]
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new_placeholder = f"Type a prompt for {selected_lora['title']}"
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with calculateDuration(f"Loading LoRA weights for {selected_lora['title']}"):
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if "weights" in selected_lora:
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pipe.load_lora_weights(lora_path, weight_name=selected_lora["weights"])
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#pipe.fuse_lora()
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else:
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pipe.load_lora_weights(lora_path)
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#pipe.fuse_lora()
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# Set random seed for reproducibility
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with calculateDuration("Randomizing seed"):
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if randomize_seed:
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image = generate_image(prompt, trigger_word, steps, seed, cfg_scale, width, height, lora_scale, progress)
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pipe.to("cpu")
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#pipe.unfuse_lora()
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pipe.unload_lora_weights()
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return image, seed
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def get_huggingface_safetensors(link):
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split_link = link.split("/")
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if(len(split_link) == 2):
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model_card = ModelCard.load(link)
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image_path = model_card.data.get("widget", [{}])[0].get("output", {}).get("url", None)
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trigger_word = model_card.data.get("instance_prompt", "")
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image_url = f"https://huggingface.co/{link}/resolve/main/{image_path}" if image_path else None
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fs = HfFileSystem()
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try:
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list_of_files = fs.ls(link, detail=False)
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for file in list_of_files:
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if(file.endswith(".safetensors")):
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safetensors_name = file.split("/")[-1]
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if (not image_url and file.lower().endswith((".jpg", ".jpeg", ".png", ".webp"))):
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image_elements = file.split("/")
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image_url = f"https://huggingface.co/{link}/resolve/main/{image_elements[-1]}"
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except Exception as e:
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print(e)
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gr.Warning(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA {e}")
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raise Exception(f"You didn't include a link neither a valid Hugging Face repository with a *.safetensors LoRA {e}")
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return split_link[1], link, safetensors_name, trigger_word, image_url
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def check_custom_model(link):
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if(link.startswith("https://")):
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if(link.startswith("https://huggingface.co") or link.startswith("https://www.huggingface.co")):
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link_split = link.split("huggingface.co/")
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return get_huggingface_safetensors(link_split[1])
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else:
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return get_huggingface_safetensors(link)
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def add_custom_lora(custom_lora):
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global loras
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if(custom_lora):
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try:
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title, repo, path, trigger_word, image = check_custom_model(custom_lora)
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card = f'''
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<div class="custom_lora_card">
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<span>Loaded custom LoRA:</span>
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<div class="card_internal">
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<img src="{image}" />
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<div>
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<h3>{title}</h3>
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<small>{"Using: <code><b>"+trigger_word+"</code></b> as the trigger word" if trigger_word else "No trigger word found. If there's a trigger word, include it in your prompt"}<br></small>
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</div>
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</div>
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</div>
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'''
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existing_item_index = next((index for (index, item) in enumerate(loras) if item['repo'] == repo), None)
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if(not existing_item_index):
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new_item = {
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"image": image,
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"title": title,
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"repo": repo,
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"weights": path,
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"trigger_word": trigger_word
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}
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print(new_item)
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existing_item_index = len(loras)
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loras.append(new_item)
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return gr.update(visible=True, value=card), gr.update(visible=True), gr.Gallery(selected_index=None), f"Custom: {path}", existing_item_index
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except Exception as e:
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gr.Warning(f"Invalid LoRA: either you entered an invalid link, or a non-FLUX LoRA")
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return gr.update(visible=True, value=f"Invalid LoRA: either you entered an invalid link, a non-FLUX LoRA"), gr.update(visible=True), gr.update(), "", None
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else:
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return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None
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def remove_custom_lora():
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return gr.update(visible=False), gr.update(visible=False), gr.update(), "", None, ""
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run_lora.zerogpu = True
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css = '''
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#title h1{font-size: 3em; display:inline-flex; align-items:center}
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#title img{width: 100px; margin-right: 0.5em}
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#gallery .grid-wrap{height: 10vh}
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#lora_list{background: var(--block-background-fill);padding: 0 1em .3em; font-size: 90%}
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.card_internal{display: flex;height: 100px;margin-top: .5em}
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.card_internal img{margin-right: 1em}
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.styler{--form-gap-width: 0px !important}
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'''
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with gr.Blocks(theme=gr.themes.Soft(), css=css) as app:
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title = gr.HTML(
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columns=3,
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elem_id="gallery"
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)
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with gr.Group():
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custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path", placeholder="multimodalart/vintage-ads-flux")
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gr.Markdown("[Check the list of FLUX LoRas](https://huggingface.co/models?other=base_model:adapter:black-forest-labs/FLUX.1-dev)", elem_id="lora_list")
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custom_lora_info = gr.HTML(visible=False)
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custom_lora_button = gr.Button("Remove custom LoRA", visible=False)
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with gr.Column(scale=4):
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result = gr.Image(label="Generated Image")
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inputs=[width, height],
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outputs=[prompt, selected_info, selected_index, width, height]
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)
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custom_lora.input(
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add_custom_lora,
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inputs=[custom_lora],
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outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index]
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)
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custom_lora_button.click(
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remove_custom_lora,
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outputs=[custom_lora_info, custom_lora_button, gallery, selected_info, selected_index, custom_lora]
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)
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gr.on(
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triggers=[generate_button.click, prompt.submit],
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fn=run_lora,
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