Update app.py (#6)

- Update app.py (9a761e3a59bcdbd6ba472d525b4ed93c89a7ecf2)

app.py

@@ -5,71 +5,56 @@
 import gradio as gr
 import numpy as np
 import random
-
 import spaces
-from diffusers import DiffusionPipeline
 import torch
+from diffusers import DiffusionPipeline
 
+dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/stable-diffusion-3.5-medium"
 
-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)
-pipe = pipe.to(device)
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype).to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1440
+MAX_IMAGE_SIZE = 2048
 
-@spaces.GPU(duration=65)
-def infer(
-    prompt,
-    negative_prompt="",
-    seed=42,
-    randomize_seed=False,
-    width=1024,
-    height=1024,
-    guidance_scale=5,
-    num_inference_steps=40,
-    progress=gr.Progress(track_tqdm=True),
-):
+@spaces.GPU()
+def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, 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]
-
+            prompt = prompt, 
+            width = width,
+            height = height,
+            num_inference_steps = num_inference_steps, 
+            generator = generator,
+            guidance_scale=0.0
+    ).images[0] 
     return image, seed
-
-
+ 
 examples = [
-        "A capybara wearing a suit holding a sign that reads Hello World",
+    "a tiny astronaut hatching from an egg on the moon",
+    "a cat holding a sign that says hello world",
+    "an anime illustration of a wiener schnitzel",
 ]
 
-css = """
+css="""
 #col-container {
     margin: 0 auto;
-    max-width: 640px;
+    max-width: 520px;
 }
 """
 
 with gr.Blocks(css=css) as demo:
+    
     with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # [Stable Diffusion 3.5 Medium (2.6B)](https://huggingface.co/stabilityai/stable-diffusion-3.5-medium)")
-        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-medium) to run locally with ComfyUI or diffusers.")
+        gr.Markdown(f"""# FLUX.1 [schnell]
+12B param rectified flow transformer distilled from [FLUX.1 [pro]](https://blackforestlabs.ai/) for 4 step generation
+[[blog](https://blackforestlabs.ai/announcing-black-forest-labs/)] [[model](https://huggingface.co/black-forest-labs/FLUX.1-schnell)]
+        """)
+        
         with gr.Row():
+            
             prompt = gr.Text(
                 label="Prompt",
                 show_label=False,
@@ -77,19 +62,13 @@ with gr.Blocks(css=css) as demo:
                 placeholder="Enter your prompt",
                 container=False,
             )
-
-            run_button = gr.Button("Run", scale=0, variant="primary")
-
+            
+            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",
-                visible=False,
-            )
-
+            
             seed = gr.Slider(
                 label="Seed",
                 minimum=0,
@@ -97,59 +76,51 @@ with gr.Blocks(css=css) as demo:
                 step=1,
                 value=0,
             )
-
+            
             randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-
+            
             with gr.Row():
+                
                 width = gr.Slider(
                     label="Width",
-                    minimum=512,
+                    minimum=256,
                     maximum=MAX_IMAGE_SIZE,
                     step=32,
-                    value=1024, 
+                    value=1024,
                 )
-
+                
                 height = gr.Slider(
                     label="Height",
-                    minimum=512,
+                    minimum=256,
                     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=4.5,
-                )
-
+                
+  
                 num_inference_steps = gr.Slider(
                     label="Number of inference steps",
                     minimum=1,
                     maximum=50,
                     step=1,
-                    value=40, 
+                    value=4,
                 )
+        
+        gr.Examples(
+            examples = examples,
+            fn = infer,
+            inputs = [prompt],
+            outputs = [result, seed],
+            cache_examples="lazy"
+        )
 
-        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],
+        fn = infer,
+        inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps],
+        outputs = [result, seed]
     )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()