sd3?

app.py

@@ -6,6 +6,13 @@ import spaces
 import os
 import uuid
 from pydub import AudioSegment
+import numpy as np
+import random
+import torch
+from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, FlowMatchEulerDiscreteScheduler
+
+
+'''AUDIO'''
 
 # Importing the model-related functions
 from stable_audio_tools import get_pretrained_model
@@ -90,6 +97,37 @@ def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
     # Return the path to the generated audio file
     return full_path_mp3
 
+'''DIFFUSION'''
+device = "cuda" if torch.cuda.is_available() else "cpu"
+dtype = torch.float16
+
+repo = "stabilityai/stable-diffusion-3-medium-diffusers"
+pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=torch.float16).to(device)
+
+MAX_SEED = np.iinfo(np.int32).max
+MAX_IMAGE_SIZE = 1344
+
+@spaces.GPU
+def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, 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
+
+'''
 # Setting up the Gradio Interface
 interface = gr.Interface(
     fn=generate_audio,
@@ -102,9 +140,80 @@ interface = gr.Interface(
     outputs=gr.Audio(type="filepath", label="Generated Audio"),
     title="Stable Audio Generator",
     description="Generate variable-length stereo audio at 44.1kHz from text prompts using Stable Audio Open 1.0.",
-)
+)'''
+
+with gr.Blocks() as demo:
+    with gr.Tab("SD3"):
+        with gr.Column:
+            gr.Markdown(f"""
+            # Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)
+            Learn more about the [Stable Diffusion 3 series](https://stability.ai/news/stable-diffusion-3). Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), [Stable Assistant](https://stability.ai/stable-assistant), or on Discord via [Stable Artisan](https://stability.ai/stable-artisan). Run locally with [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [diffusers](https://github.com/huggingface/diffusers)
+            """)
+        with gr.Row():
+            prompt = gr.Text(
+                label="Prompt",
+                show_label=False,
+                max_lines=1,
+                placeholder="Enter your prompt",
+                container=False,
+            )
+            run_button = gr.Button("Run", scale=0)
+        result = gr.Image(label="Result", show_label=False)
+
+        with gr.Accordion("Advanced Settings", open=False):
+            
+            negative_prompt = gr.Text(
+                label="Negative prompt",
+                max_lines=1,
+                placeholder="Enter a negative prompt",
+            )
+            
+            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=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=64,
+                    value=1024,
+                )
+                
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=64,
+                    value=1024,
+                )
+            
+            with gr.Row():
+                
+                guidance_scale = gr.Slider(
+                    label="Guidance scale",
+                    minimum=0.0,
+                    maximum=10.0,
+                    step=0.1,
+                    value=5.0,
+                )
+                
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=28,
+                )
 
-with gr.Blocks() as demo:                
     with gr.Tab("Audio"):
         audio_prompt =  gr.Textbox(label="Prompt", placeholder="Enter your text prompt here")
         audio_duration = gr.Slider(0, 47, value=30, label="Duration in Seconds")
@@ -114,6 +223,12 @@ with gr.Blocks() as demo:
         audio_output = gr.Audio(type="filepath", label="Generated Audio")
     audio_process_button.click(generate_audio, [audio_prompt, audio_duration, audio_steps, audio_cfg], [audio_output])
 
+    gr.on(
+        triggers=[run_button.click, prompt.submit, negative_prompt.submit],
+        fn = infer,
+        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
+        outputs = [result, seed]
+    )
 # Pre-load the model to avoid multiprocessing issues
 model, model_config = load_model()