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1d5c6d0
1
Parent(s):
1475e41
Update app.py
Browse files
app.py
CHANGED
@@ -14,7 +14,7 @@ with open(lora_list, "r") as file:
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data = json.load(file)
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sdxl_loras = [
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{
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-
"image": item["image"],
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"title": item["title"],
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"repo": item["repo"],
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"trigger_word": item["trigger_word"],
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@@ -46,16 +46,19 @@ original_pipe = copy.deepcopy(pipe)
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#@spaces.GPU
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def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
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pipe = copy.deepcopy(original_pipe)
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pipe.load_lora_weights(shuffled_items[0]['repo'], weight_name=shuffled_items[0]['weights'])
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pipe.fuse_lora(lora_1_scale)
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pipe.load_lora_weights(shuffled_items[1]['repo'], weight_name=shuffled_items[1]['weights'])
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pipe.fuse_lora(lora_2_scale)
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-
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pipe.to(torch_dtype=torch.float16)
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pipe.to("cuda")
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if negative_prompt == "":
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negative_prompt = False
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image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=25, guidance_scale=7).images[0]
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return image
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@@ -86,12 +89,12 @@ with gr.Blocks(css=css) as demo:
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)
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with gr.Row():
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with gr.Column(min_width=10, scale=6):
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lora_1 = gr.Image(interactive=False, height=
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lora_1_prompt = gr.Markdown()
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with gr.Column(min_width=10, scale=1, elem_id="plus_column"):
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plus = gr.HTML("+", elem_id="plus_button")
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with gr.Column(min_width=10, scale=6):
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lora_2 = gr.Image(interactive=False, height=
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lora_2_prompt = gr.Markdown()
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with gr.Row():
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prompt = gr.Textbox(label="Your prompt", info="arrange the trigger words of the two LoRAs in a coherent sentence", interactive=True, elem_id="prompt")
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data = json.load(file)
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sdxl_loras = [
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{
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"image": item["image"] if item["image"].startswith("https://") else f"https://huggingface.co/spaces/multimodalart/LoraTheExplorer/resolve/main/{item["image"]}",
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"title": item["title"],
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"repo": item["repo"],
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"trigger_word": item["trigger_word"],
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#@spaces.GPU
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def merge_and_run(prompt, negative_prompt, shuffled_items, lora_1_scale=0.5, lora_2_scale=0.5, progress=gr.Progress(track_tqdm=True)):
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print("Copying pipe")
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pipe = copy.deepcopy(original_pipe)
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print("Loading LoRAs")
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pipe.load_lora_weights(shuffled_items[0]['repo'], weight_name=shuffled_items[0]['weights'])
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pipe.fuse_lora(lora_1_scale)
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pipe.load_lora_weights(shuffled_items[1]['repo'], weight_name=shuffled_items[1]['weights'])
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pipe.fuse_lora(lora_2_scale)
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+
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pipe.to(torch_dtype=torch.float16)
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pipe.to("cuda")
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if negative_prompt == "":
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negative_prompt = False
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print("Running inference")
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image = pipe(prompt=prompt, negative_prompt=negative_prompt, num_inference_steps=25, guidance_scale=7).images[0]
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return image
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)
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with gr.Row():
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with gr.Column(min_width=10, scale=6):
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lora_1 = gr.Image(interactive=False, height=300)
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lora_1_prompt = gr.Markdown()
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with gr.Column(min_width=10, scale=1, elem_id="plus_column"):
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plus = gr.HTML("+", elem_id="plus_button")
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with gr.Column(min_width=10, scale=6):
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lora_2 = gr.Image(interactive=False, height=300)
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lora_2_prompt = gr.Markdown()
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with gr.Row():
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prompt = gr.Textbox(label="Your prompt", info="arrange the trigger words of the two LoRAs in a coherent sentence", interactive=True, elem_id="prompt")
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