TheAwakenOne commited on
Commit
44f98f9
1 Parent(s): b64cb38

Updated app with random seed and 25 fixed steps

Browse files
Files changed (1) hide show
  1. app.py +9 -8
app.py CHANGED
@@ -3,8 +3,9 @@ import torch
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  from diffusers import FluxPipeline
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  from huggingface_hub import HfApi
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  import spaces
 
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- @spaces.GPU(duration=70) # Allocate GPU for 70 seconds
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  def initialize_model():
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  model_id = "Freepik/flux.1-lite-8B-alpha"
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  pipe = FluxPipeline.from_pretrained(
@@ -17,14 +18,16 @@ def initialize_model():
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  def generate_image(
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  prompt,
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  guidance_scale=3.5,
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- num_steps=28,
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- seed=11,
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  width=1024,
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  height=1024
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  ):
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  # Initialize model within the GPU context
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  pipe = initialize_model()
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  with torch.inference_mode():
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  image = pipe(
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  prompt=prompt,
@@ -43,17 +46,15 @@ demo = gr.Interface(
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  inputs=[
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  gr.Textbox(label="Prompt", placeholder="Enter your image description here..."),
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  gr.Slider(minimum=1, maximum=20, value=3.5, label="Guidance Scale", step=0.5),
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- gr.Slider(minimum=1, maximum=50, value=28, label="Number of Steps", step=1),
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- gr.Slider(minimum=1, maximum=1000000, value=11, label="Seed", step=1),
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  gr.Slider(minimum=128, maximum=1024, value=1024, label="Width", step=64),
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  gr.Slider(minimum=128, maximum=1024, value=1024, label="Height", step=64)
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  ],
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  outputs=gr.Image(type="pil", label="Generated Image"),
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  title="Flux Image Generator (Zero-GPU)",
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- description="Generate images using Freepik's Flux model with Zero-GPU allocation",
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  examples=[
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- ["A close-up image of a green alien with fluorescent skin in the middle of a dark purple forest", 3.5, 28, 11, 1024, 1024],
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- ["A serene landscape with mountains at sunset", 3.5, 28, 42, 1024, 1024],
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  ]
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  )
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  from diffusers import FluxPipeline
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  from huggingface_hub import HfApi
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  import spaces
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+ import random
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+ @spaces.GPU(duration=70)
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  def initialize_model():
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  model_id = "Freepik/flux.1-lite-8B-alpha"
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  pipe = FluxPipeline.from_pretrained(
 
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  def generate_image(
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  prompt,
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  guidance_scale=3.5,
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+ num_steps=25, # Changed default to 25
 
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  width=1024,
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  height=1024
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  ):
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  # Initialize model within the GPU context
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  pipe = initialize_model()
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+ # Generate random seed
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+ seed = random.randint(1, 1000000)
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+
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  with torch.inference_mode():
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  image = pipe(
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  prompt=prompt,
 
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  inputs=[
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  gr.Textbox(label="Prompt", placeholder="Enter your image description here..."),
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  gr.Slider(minimum=1, maximum=20, value=3.5, label="Guidance Scale", step=0.5),
 
 
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  gr.Slider(minimum=128, maximum=1024, value=1024, label="Width", step=64),
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  gr.Slider(minimum=128, maximum=1024, value=1024, label="Height", step=64)
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  ],
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  outputs=gr.Image(type="pil", label="Generated Image"),
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  title="Flux Image Generator (Zero-GPU)",
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+ description="Generate images using Freepik's Flux model with Zero-GPU allocation. Using 25 steps and random seed for each generation.",
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  examples=[
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+ ["A close-up image of a green alien with fluorescent skin in the middle of a dark purple forest", 3.5, 1024, 1024],
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+ ["A serene landscape with mountains at sunset", 3.5, 1024, 1024],
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  ]
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  )
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