Update app.py

app.py

@@ -1,18 +1,19 @@
 import torch
 import gradio as gr
-from diffusers import Flux2KleinPipeline
+from diffusers import StableDiffusionPipeline
 from tqdm import tqdm
 
 device = "cpu"
-dtype = torch.bfloat16
+dtype = torch.bfloat16  # si souci, mets torch.float32
 
-pipe = Flux2KleinPipeline.from_pretrained(
-    "black-forest-labs/FLUX.2-klein-4B",
+pipe = StableDiffusionPipeline.from_pretrained(
+    "SG161222/Realistic_Vision_V6.0_B1_noVAE",
     torch_dtype=dtype,
     low_cpu_mem_usage=True,
-    token=None
 )
 
+pipe.enable_sequential_cpu_offload()
+
 def generate_image(prompt, progress=gr.Progress(track_tqdm=True)):
     with torch.inference_mode():
         progress(0, desc="Initialisation...")
@@ -24,14 +25,14 @@ def generate_image(prompt, progress=gr.Progress(track_tqdm=True)):
 
         image = pipe(
             prompt=prompt,
-            height=384,
-            width=384,
-            guidance_scale=1.0,
-            num_inference_steps=4,
+            height=512,
+            width=512,
+            guidance_scale=7.0,
+            num_inference_steps=25,
         ).images[0]
 
         progress(1.0, desc="Terminé !")
-        image.save("flux-klein.png")
+        image.save("realistic-vision.png")
         return image
 
 css = """
@@ -53,8 +54,8 @@ demo = gr.Interface(
     fn=generate_image,
     inputs=gr.Textbox(label="Prompt", placeholder="Décris ton image...", lines=2),
     outputs=gr.Image(label="Image générée"),
-    title="Flux.2 Klein — Mode CPU 12 Go",
-    description="Version optimisée pour machines sans GPU",
+    title="Realistic Vision — CPU",
+    description="SD 1.5 photoréaliste, très propre, CPU only",
     css=css,
 )