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44f98f9
1
Parent(s):
b64cb38
Updated app with random seed and 25 fixed steps
Browse files
app.py
CHANGED
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@@ -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)
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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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@@ -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=
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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,
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@@ -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,
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["A serene landscape with mountains at sunset", 3.5,
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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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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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