Kvikontent commited on
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3c33543
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1 Parent(s): e16f7e6

Update app.py

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Files changed (1) hide show
  1. app.py +13 -2
app.py CHANGED
@@ -12,18 +12,29 @@ pipe.enable_model_cpu_offload()
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  pipe.enable_vae_slicing()
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  @spaces.GPU(duration=250)
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- def generate(prompt):
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- video_frames = pipe(prompt, num_inference_steps=50, num_frames=200).frames[0]
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  video_path = export_to_video(video_frames, fps=10)
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  return video_path
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  prompt = gr.Textbox(label="Enter prompt to generate a video", info="Based on this prompt ai will generate a video")
 
 
 
 
 
 
 
 
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  interface = gr.Interface(
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  generate,
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  inputs=[prompt],
 
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  examples=[["Astronaut riding a horse"], ["Darth vader surfing in waves"]],
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  outputs="video",
 
 
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  cache_examples=False,
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  theme="soft"
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  ).launch()
 
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  pipe.enable_vae_slicing()
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  @spaces.GPU(duration=250)
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+ def generate(prompt, num_inference_steps, num_frames):
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+ video_frames = pipe(prompt, num_inference_steps, num_frames).frames[0]
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  video_path = export_to_video(video_frames, fps=10)
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  return video_path
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  prompt = gr.Textbox(label="Enter prompt to generate a video", info="Based on this prompt ai will generate a video")
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+ description="""
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+ πŸš€ This is **unofficial** demo of Openai's Sora that haven't been released yet.
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+ βœ” This space made using [ali-vilab/text-to-video-ms-1.7b](https://huggingface.co/ali-vilab/text-to-video-ms-1.7b)
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+ ⌚ Estimated generation time is **150 seconds**
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+ 🎁 Space is running on ZeroGPU, if you want faster generation, duplicate space and choose faster GPU
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+ """
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+ num_inference_steps=gr.Slider(8, 64, step=8, value=24, label="Num Inference Steps", info="More steps then better quality")
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+ num_frames=gr.Slider(8, 640, step=8, value=200, label="Num of Frames", info="It is duration of video")
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  interface = gr.Interface(
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  generate,
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  inputs=[prompt],
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+ additional_inputs=[num_inference_steps, num_frames],
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  examples=[["Astronaut riding a horse"], ["Darth vader surfing in waves"]],
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  outputs="video",
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+ title="Openai Sora (Unofficial)",
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+ description=description,
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  cache_examples=False,
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  theme="soft"
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  ).launch()