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Parent(s):
c5d7772
Update app.py
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app.py
CHANGED
@@ -10,7 +10,7 @@ from time import sleep
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import copy
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import json
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import gc
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with open("sdxl_loras.json", "r") as file:
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data = json.load(file)
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sdxl_loras = [
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@@ -23,6 +23,8 @@ with open("sdxl_loras.json", "r") as file:
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"is_compatible": item["is_compatible"],
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"is_pivotal": item.get("is_pivotal", False),
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"text_embedding_weights": item.get("text_embedding_weights", None),
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"is_nc": item.get("is_nc", False)
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}
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for item in data
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@@ -41,6 +43,8 @@ for item in sdxl_loras:
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item["saved_name"] = saved_name
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item["state_dict"] = state_dict #{k: v.to(device=device, dtype=torch.float16) for k, v in state_dict.items() if torch.is_tensor(v)}
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vae = AutoencoderKL.from_pretrained(
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"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
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)
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@@ -55,7 +59,7 @@ pipe.to(device)
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last_lora = ""
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last_merged = False
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last_fused = False
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def update_selection(selected_state: gr.SelectData):
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lora_repo = sdxl_loras[selected_state.index]["repo"]
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instance_prompt = sdxl_loras[selected_state.index]["trigger_word"]
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new_placeholder = "Type a prompt. This LoRA applies for all prompts, no need for a trigger word" if instance_prompt == "" else "Type a prompt to use your selected LoRA"
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@@ -135,7 +139,7 @@ def merge_incompatible_lora(full_path_lora, lora_scale):
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del lora_model
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gc.collect()
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def run_lora(prompt, negative, lora_scale, selected_state, progress=gr.Progress(track_tqdm=True)):
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global last_lora, last_merged, last_fused, pipe
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if negative == "":
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@@ -195,6 +199,17 @@ def run_lora(prompt, negative, lora_scale, selected_state, progress=gr.Progress(
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gc.collect()
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return image, gr.update(visible=True)
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with gr.Blocks(css="custom.css") as demo:
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title = gr.HTML(
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@@ -203,14 +218,16 @@ with gr.Blocks(css="custom.css") as demo:
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)
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selected_state = gr.State()
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with gr.Row():
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with gr.Column():
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prompt_title = gr.Markdown(
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value="### Click on a LoRA in the gallery to select it",
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@@ -268,9 +285,15 @@ with gr.Blocks(css="custom.css") as demo:
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submit_disclaimer = gr.Markdown(
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"This is a curated gallery by me, [apolinário (multimodal.art)](https://twitter.com/multimodalart). I'll try to include as many cool LoRAs as they are submitted! You can [duplicate this Space](https://huggingface.co/spaces/multimodalart/LoraTheExplorer?duplicate=true) to use it privately, and add your own LoRAs by editing `sdxl_loras.json` in the Files tab of your private space."
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)
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gallery.select(
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update_selection,
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outputs=[prompt_title, prompt, prompt, selected_state, use_diffusers, use_uis],
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queue=False,
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show_progress=False,
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@@ -282,7 +305,7 @@ with gr.Blocks(css="custom.css") as demo:
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show_progress=False
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).success(
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fn=run_lora,
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inputs=[prompt, negative, weight, selected_state],
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outputs=[result, share_group],
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)
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button.click(
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@@ -296,6 +319,6 @@ with gr.Blocks(css="custom.css") as demo:
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outputs=[result, share_group],
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)
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share_button.click(None, [], [], _js=share_js)
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demo.queue(max_size=20)
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demo.launch()
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import copy
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import json
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import gc
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import random
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with open("sdxl_loras.json", "r") as file:
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data = json.load(file)
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sdxl_loras = [
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"is_compatible": item["is_compatible"],
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"is_pivotal": item.get("is_pivotal", False),
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"text_embedding_weights": item.get("text_embedding_weights", None),
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"likes": item.get("likes", 0),
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"downloads": item.get("downloads", 0),
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"is_nc": item.get("is_nc", False)
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}
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for item in data
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item["saved_name"] = saved_name
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item["state_dict"] = state_dict #{k: v.to(device=device, dtype=torch.float16) for k, v in state_dict.items() if torch.is_tensor(v)}
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gr_sdxl_loras = gr.State(value=sdxl_loras)
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vae = AutoencoderKL.from_pretrained(
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"madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16
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)
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last_lora = ""
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last_merged = False
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last_fused = False
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def update_selection(selected_state: gr.SelectData, sdxl_loras):
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lora_repo = sdxl_loras[selected_state.index]["repo"]
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instance_prompt = sdxl_loras[selected_state.index]["trigger_word"]
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new_placeholder = "Type a prompt. This LoRA applies for all prompts, no need for a trigger word" if instance_prompt == "" else "Type a prompt to use your selected LoRA"
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del lora_model
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gc.collect()
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def run_lora(prompt, negative, lora_scale, selected_state, sdxl_loras, progress=gr.Progress(track_tqdm=True)):
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global last_lora, last_merged, last_fused, pipe
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if negative == "":
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gc.collect()
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return image, gr.update(visible=True)
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def shuffle_gallery(sdxl_loras):
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random.shuffle(sdxl_loras)
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return [(item["image"], item["title"]) for item in sdxl_loras], sdxl_loras
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def swap_gallery(order, sdxl_loras):
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if(order == "random"):
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return shuffle_gallery(sdxl_loras)
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else:
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sorted_gallery = sorted(sdxl_loras, key=lambda x: x.get(order, 0), reverse=True)
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return [(item["image"], item["title"]) for item in sorted_gallery], sdxl_loras
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with gr.Blocks(css="custom.css") as demo:
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title = gr.HTML(
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)
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selected_state = gr.State()
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with gr.Row():
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with gr.Box():
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order_gallery = gr.Radio(choices=["random", "likes", "downloads"], value="random", label="Order by")
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gallery = gr.Gallery(
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value=[(item["image"], item["title"]) for item in sdxl_loras],
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label="SDXL LoRA Gallery",
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allow_preview=False,
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columns=3,
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elem_id="gallery",
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show_share_button=False
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)
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with gr.Column():
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prompt_title = gr.Markdown(
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value="### Click on a LoRA in the gallery to select it",
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submit_disclaimer = gr.Markdown(
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"This is a curated gallery by me, [apolinário (multimodal.art)](https://twitter.com/multimodalart). I'll try to include as many cool LoRAs as they are submitted! You can [duplicate this Space](https://huggingface.co/spaces/multimodalart/LoraTheExplorer?duplicate=true) to use it privately, and add your own LoRAs by editing `sdxl_loras.json` in the Files tab of your private space."
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)
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order_gallery.change(
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fn=swap_gallery,
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inputs=[order_gallery, gr_sdxl_loras],
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outputs=[gallery, gr_sdxl_loras],
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queue=False
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)
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gallery.select(
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update_selection,
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inputs=[gr_sdxl_loras],
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outputs=[prompt_title, prompt, prompt, selected_state, use_diffusers, use_uis],
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queue=False,
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show_progress=False,
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show_progress=False
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).success(
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fn=run_lora,
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inputs=[prompt, negative, weight, selected_state, gr_sdxl_loras],
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outputs=[result, share_group],
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)
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button.click(
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outputs=[result, share_group],
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)
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share_button.click(None, [], [], _js=share_js)
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demo.load(fn=shuffle_gallery, inputs=[gr_sdxl_loras], outputs=[gallery, gr_sdxl_loras], queue=False)
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demo.queue(max_size=20)
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demo.launch(share=True)
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