send it

app.py

@@ -1,60 +1,146 @@
 import gradio as gr
-import torch
+import numpy as np
+import random
 import spaces
-from diffusers import FluxPipeline
+import torch
+from diffusers import DiffusionPipeline
 
+# Define constants
+dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
-dtype = torch.float16 if torch.cuda.is_available() else torch.float32
-
-MODEL_ID = "drbaph/FLUX.1-schnell-dev-merged-fp8-4step"
-MODEL_FILE = "flux1-schnell-dev-merged-fp8-4step.safetensors"
-
-def load_model():
-    pipe = FluxPipeline.from_single_file(
-        f"https://huggingface.co/{MODEL_ID}/resolve/main/{MODEL_FILE}",
-        torch_dtype=dtype
-    )
-    pipe.to(device)
-    return pipe
-
-pipe = load_model()
-
-MAX_SEED = 2**32 - 1
+MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
 
+# Load the diffusion pipeline
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype).to(device)
+
 @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 = torch.randint(0, MAX_SEED, (1,)).item()
-    generator = torch.Generator(device=device).manual_seed(seed)
+        seed = random.randint(0, MAX_SEED)
+    generator = torch.Generator().manual_seed(seed)
     image = pipe(
-        prompt=prompt,
+        prompt=prompt, 
         width=width,
         height=height,
-        num_inference_steps=num_inference_steps,
+        num_inference_steps=num_inference_steps, 
         generator=generator,
-        guidance_scale=0.0,
-        max_sequence_length=256
+        guidance_scale=0.0
     ).images[0]
     return image, seed
 
-# Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown("# FLUX.1 [schnell-dev-merged-fp8-4step]")
-    with gr.Row():
-        prompt = gr.Textbox(label="Prompt")
-        run_button = gr.Button("Generate")
-    with gr.Row():
-        result = gr.Image(label="Generated Image")
-        seed_output = gr.Number(label="Seed Used")
-    with gr.Accordion("Advanced Settings", open=False):
-        seed = gr.Slider(label="Seed", minimum=0, maximum=MAX_SEED, step=1, value=42)
-        randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-        width = gr.Slider(label="Width", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
-        height = gr.Slider(label="Height", minimum=256, maximum=MAX_IMAGE_SIZE, step=32, value=1024)
-        num_inference_steps = gr.Slider(label="Number of inference steps", minimum=1, maximum=10, step=1, value=4)
+# Define example prompts
+examples = [
+    "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 styling for the Japanese-inspired interface
+css = """
+body {
+    background-color: #fff;
+    font-family: 'Noto Sans JP', sans-serif;
+    color: #333;
+}
+#col-container {
+    margin: 0 auto;
+    max-width: 520px;
+    border: 2px solid #000;
+    padding: 20px;
+    background-color: #f7f7f7;
+    border-radius: 10px;
+}
+.gr-button {
+    background-color: #e60012;
+    color: #fff;
+    border: 2px solid #000;
+}
+.gr-button:hover {
+    background-color: #c20010;
+}
+.gr-slider, .gr-checkbox, .gr-textbox {
+    border: 2px solid #000;
+}
+.gr-accordion {
+    border: 2px solid #000;
+    background-color: #fff;
+}
+.gr-image {
+    border: 2px solid #000;
+}
+"""
+
+# Create the Gradio interface
+with gr.Blocks(css=css) as demo:
     
-    inputs = [prompt, seed, randomize_seed, width, height, num_inference_steps]
-    run_button.click(fn=infer, inputs=inputs, outputs=[result, seed_output])
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("""
+        # 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.Textbox(
+                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):
+            seed = gr.Slider(
+                label="Seed",
+                minimum=0,
+                maximum=MAX_SEED,
+                step=1,
+                value=42,
+            )
+            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
+
+            with gr.Row():
+                width = gr.Slider(
+                    label="Width",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+                height = gr.Slider(
+                    label="Height",
+                    minimum=256,
+                    maximum=MAX_IMAGE_SIZE,
+                    step=32,
+                    value=1024,
+                )
+
+            with gr.Row():
+                num_inference_steps = gr.Slider(
+                    label="Number of inference steps",
+                    minimum=1,
+                    maximum=50,
+                    step=1,
+                    value=4,
+                )
+
+        gr.Examples(
+            examples=examples,
+            fn=infer,
+            inputs=[prompt],
+            outputs=[result, seed],
+            cache_examples="lazy"
+        )
+
+    gr.on(
+        triggers=[run_button.click, prompt.submit],
+        fn=infer,
+        inputs=[prompt, seed, randomize_seed, width, height, num_inference_steps],
+        outputs=[result, seed]
+    )
 
-demo.launch()
+demo.launch()

requirements.txt

@@ -2,6 +2,6 @@ accelerate
 diffusers
 invisible_watermark
 torch
-transformers==4.42.4
+transformers
 xformers
 sentencepiece