v1

README.md

@@ -1,12 +1,14 @@
 ---
-title: SD3.5 Large
-emoji: 🌖
-colorFrom: green
-colorTo: pink
+title: Stable Diffusion 3.5 Large Turbo
+emoji: 🏃
+colorFrom: purple
+colorTo: blue
 sdk: gradio
-sdk_version: 5.22.0
+sdk_version: 5.3.0
 app_file: app.py
-pinned: false
+pinned: true
+license: other
+short_description: Generate images with SD3.5
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,153 @@
+import gradio as gr
+import numpy as np
+import random
+import os
+import spaces
+from diffusers import DiffusionPipeline
+import torch
+from huggingface_hub import login
+login(os.getenv("HF_TOKEN"))
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model_repo_id = "stabilityai/stable-diffusion-3.5-large"
+
+if torch.cuda.is_available():
+    torch_dtype = torch.bfloat16
+else:
+    torch_dtype = torch.float32
+
+pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype, use_safetensors=True)
+if torch.cuda.is_available():
+    pipe = pipe.to(device, dtype=torch.bfloat16)
+    torch_dtype = torch.bfloat16
+else :
+    pipe = pipe.to(device, dtype=torch.float32)
+    torch_dtype = torch.float32
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1024
+
+@spaces.GPU
+def infer(
+    prompt,
+    negative_prompt="",
+    seed=42,
+    randomize_seed=False,
+    width=1024,
+    height=1024,
+    guidance_scale=0.0,
+    num_inference_steps=4,
+    progress=gr.Progress(track_tqdm=True),
+):
+    if randomize_seed:
+        seed = random.randint(0, MAX_SEED)
+
+    generator = torch.Generator().manual_seed(seed)
+
+    image = pipe(
+        prompt=prompt,
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale,
+        num_inference_steps=num_inference_steps,
+        width=width,
+        height=height,
+        generator=generator,
+    ).images[0]
+
+    return image, seed
+
+
+examples = [
+        "A capybara wearing a suit holding a sign that reads Hello World",
+]
+
+css = """
+#col-container {
+    margin: 0 auto;
+    max-width: 640px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown(" # Stable Diffusion 3.5 Large Turbo (8B)")
+        
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                max_lines=5,
+                placeholder="Enter your prompt",
+            )
+            negative_prompt = gr.Text(
+                label="Negative prompt",
+                max_lines=5,
+                placeholder="Enter a negative prompt",
+            )
+            run_button = gr.Button("Run", scale=0, variant="primary")
+
+        result = gr.Image(label="Result", show_label=False)
+
+        with gr.Accordion("Advanced Settings", open=False):
+            
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=0,
+            )
+
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=512,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024, 
+                )
+
+                height = gr.Slider(
+                    label="Height",
+                    minimum=512,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+
+            with gr.Row():
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=0.0,
+                    maximum=7.5,
+                    step=0.1,
+                    value=0.0,
+                )
+
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=4, 
+                )
+
+        gr.Examples(examples=examples, inputs=[prompt], outputs=[result, seed], fn=infer, cache_examples=True, cache_mode="lazy")
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[
+            prompt,
+            negative_prompt,
+            seed,
+            randomize_seed,
+            width,
+            height,
+            guidance_scale,
+            num_inference_steps,
+        ],
+        outputs=[result, seed],
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,6 @@
+accelerate
+diffusers
+torch
+transformers
+git+https://github.com/huggingface/diffusers.git
+sentencepiece