hotbiz commited on
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383b4fc
1 Parent(s): 681e005

Update app.py

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  1. app.py +0 -118
app.py CHANGED
@@ -1,123 +1,5 @@
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  import gradio as gr
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- import numpy as np
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- import random
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- import spaces
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- import torch
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- from diffusers import DiffusionPipeline
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- dtype = torch.bfloat16
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- device = "cuda" if torch.cuda.is_available() else "cpu"
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-
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- pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype).to(device)
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-
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- MAX_SEED = np.iinfo(np.int32).max
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- MAX_IMAGE_SIZE = 2048
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-
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- @spaces.GPU()
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- def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_inference_steps=4, progress=gr.Progress(track_tqdm=True)):
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- if randomize_seed:
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- seed = random.randint(0, MAX_SEED)
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- generator = torch.Generator().manual_seed(seed)
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- image = pipe(
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- prompt = prompt,
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- width = width,
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- height = height,
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- num_inference_steps = num_inference_steps,
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- generator = generator,
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- guidance_scale=0.0
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- ).images[0]
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- return image, seed
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-
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- examples = [
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- "a tiny astronaut hatching from an egg on the moon",
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- "a cat holding a sign that says hello world",
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- "an anime illustration of a wiener schnitzel",
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- ]
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-
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- css="""
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- #col-container {
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- margin: 0 auto;
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- max-width: 520px;
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- }
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- """
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-
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- with gr.Blocks(css=css) as demo:
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-
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- with gr.Column(elem_id="col-container"):
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- gr.Markdown(f"""# FLUX.1 [schnell]
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- 12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
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- [[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
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- """)
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-
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- with gr.Row():
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-
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- prompt = gr.Text(
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- label="Prompt",
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- show_label=False,
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- max_lines=1,
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- placeholder="Enter your prompt",
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- container=False,
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- )
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-
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- run_button = gr.Button("Run", scale=0)
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-
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- result = gr.Image(label="Result", show_label=False)
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-
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- with gr.Accordion("Advanced Settings", open=False):
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-
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- seed = gr.Slider(
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- label="Seed",
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- minimum=0,
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- maximum=MAX_SEED,
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- step=1,
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- value=0,
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- )
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-
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- randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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-
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- with gr.Row():
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-
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- width = gr.Slider(
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- label="Width",
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- minimum=256,
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- maximum=MAX_IMAGE_SIZE,
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- step=32,
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- value=1024,
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- )
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-
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- height = gr.Slider(
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- label="Height",
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- minimum=256,
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- maximum=MAX_IMAGE_SIZE,
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- step=32,
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- value=1024,
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- )
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-
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- with gr.Row():
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-
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-
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- num_inference_steps = gr.Slider(
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- label="Number of inference steps",
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- minimum=1,
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- maximum=50,
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- step=1,
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- value=4,
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- )
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-
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- gr.Examples(
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- examples = examples,
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- fn = infer,
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- inputs = [prompt],
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- outputs = [result, seed],
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- cache_examples="lazy"
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- )
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-
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- gr.on(
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- triggers=[run_button.click, prompt.submit],
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- fn = infer,
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- inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
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- outputs = [result, seed]
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- )
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  gr.load("models/black-forest-labs/FLUX.1-schnell").launch()
 
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  import gradio as gr
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  gr.load("models/black-forest-labs/FLUX.1-schnell").launch()