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SD3.5 Large Turbo Public Release
Browse filesCo-authored-by: multimodalart <multimodalart@users.noreply.huggingface.co>
- .gitattributes +35 -0
- README.md +14 -0
- app.py +151 -0
- requirements.txt +6 -0
.gitattributes
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README.md
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---
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title: Stable Diffusion 3.5 Large Turbo
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emoji: 🏃
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colorFrom: purple
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colorTo: blue
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sdk: gradio
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sdk_version: 5.3.0
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app_file: app.py
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pinned: true
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license: other
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short_description: Generate images fast with SD3.5 turbo
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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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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from diffusers import DiffusionPipeline
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import torch
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model_repo_id = "stabilityai/stable-diffusion-3.5-large-turbo"
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if torch.cuda.is_available():
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torch_dtype = torch.bfloat16
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else:
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torch_dtype = torch.float32
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pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
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pipe = pipe.to(device)
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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@spaces.GPU
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def infer(
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prompt,
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negative_prompt="",
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seed=42,
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randomize_seed=False,
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width=1024,
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height=1024,
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guidance_scale=0.0,
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num_inference_steps=4,
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progress=gr.Progress(track_tqdm=True),
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):
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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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negative_prompt=negative_prompt,
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guidance_scale=guidance_scale,
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num_inference_steps=num_inference_steps,
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width=width,
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height=height,
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generator=generator,
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).images[0]
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return image, seed
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examples = [
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"A capybara wearing a suit holding a sign that reads Hello World",
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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: 640px;
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Column(elem_id="col-container"):
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gr.Markdown(" # [Stable Diffusion 3.5 Large Turbo (8B)](https://huggingface.co/stabilityai/stable-diffusion-3.5-large-turbo)")
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gr.Markdown("[Learn more](https://stability.ai/news/introducing-stable-diffusion-3-5) about the Stable Diffusion 3.5 series. Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), or [download model](https://huggingface.co/stabilityai/stable-diffusion-3.5-large-turbo) to run locally with ComfyUI or diffusers.")
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with gr.Row():
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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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run_button = gr.Button("Run", scale=0, variant="primary")
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result = gr.Image(label="Result", show_label=False)
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with gr.Accordion("Advanced Settings", open=False):
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negative_prompt = gr.Text(
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label="Negative prompt",
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max_lines=1,
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placeholder="Enter a negative prompt",
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visible=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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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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with gr.Row():
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width = gr.Slider(
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label="Width",
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minimum=512,
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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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height = gr.Slider(
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label="Height",
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minimum=512,
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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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with gr.Row():
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guidance_scale = gr.Slider(
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label="Guidance scale",
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minimum=0.0,
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maximum=7.5,
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step=0.1,
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value=0.0,
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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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gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")
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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=[
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prompt,
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negative_prompt,
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seed,
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randomize_seed,
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width,
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height,
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guidance_scale,
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num_inference_steps,
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],
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outputs=[result, seed],
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)
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if __name__ == "__main__":
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demo.launch()
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requirements.txt
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accelerate
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diffusers
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torch
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transformers
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git+https://github.com/huggingface/diffusers.git
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sentencepiece
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