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Update app.py
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app.py
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@@ -3,32 +3,8 @@ from tuneavideo.models.unet import UNet3DConditionModel
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from tuneavideo.util import save_videos_grid
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import torch
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import gradio as gr
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from bs4 import BeautifulSoup
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import requests
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def model_url_list():
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url_list = []
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for i in range(0, 5):
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url_list.append(f"https://huggingface.co/models?p={i}&sort=downloads&search=dreambooth")
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return url_list
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def data_scraping(url_list):
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model_list = []
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for url in url_list:
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response = requests.get(url)
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soup = BeautifulSoup(response.text, "html.parser")
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div_class = 'grid grid-cols-1 gap-5 2xl:grid-cols-2'
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div = soup.find('div', {'class': div_class})
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for a in div.find_all('a', href=True):
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model_list.append(a['href'])
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return model_list
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model_list = data_scraping(model_url_list())
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for i in range(len(model_list)):
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model_list[i] = model_list[i][1:]
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best_model_list = [
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"runwayml/stable-diffusion-v1-5",
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"CompVis/stable-diffusion-v1-4",
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"prompthero/openjourney",
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@@ -36,8 +12,6 @@ best_model_list = [
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"dreamlike-art/dreamlike-diffusion-1.0"
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]
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model_list = best_model_list + model_list
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def tune_video_predict(
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pipe_id: str,
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prompt: str,
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from tuneavideo.util import save_videos_grid
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import torch
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import gradio as gr
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model_list = [
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"runwayml/stable-diffusion-v1-5",
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"CompVis/stable-diffusion-v1-4",
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"prompthero/openjourney",
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"dreamlike-art/dreamlike-diffusion-1.0"
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]
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def tune_video_predict(
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pipe_id: str,
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prompt: str,
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