Update app.py

app.py

@@ -3,15 +3,24 @@ from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 import torch
 from PIL import Image
 import random
+from peft import PeftModel, LoraConfig
 
-model_id = "CompVis/stable-diffusion-v1-4"  # Daha hafif bir model
-lora_model_id = "codermert/mert_flux"  # Your LoRA model
+model_id = "CompVis/stable-diffusion-v1-4"
+lora_model_id = "codermert/mert_flux"
 
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
-pipe = pipe.to("cpu")  # CPU'ya taşıyoruz
-pipe.load_lora_weights(lora_model_id)
-pipe.safety_checker = None  # Safety checker'ı devre dışı bırakıyoruz
+def load_model():
+    pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)
+    pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+    pipe = pipe.to("cpu")
+    pipe.safety_checker = None
+
+    # Load LoRA weights
+    config = LoraConfig.from_pretrained(lora_model_id)
+    pipe.unet = PeftModel.from_pretrained(pipe.unet, lora_model_id)
+    
+    return pipe
+
+pipe = load_model()
 
 def generate_image(prompt, negative_prompt, steps, cfg_scale, seed, strength):
     if seed == -1:
@@ -26,7 +35,6 @@ def generate_image(prompt, negative_prompt, steps, cfg_scale, seed, strength):
             num_inference_steps=steps,
             guidance_scale=cfg_scale,
             generator=generator,
-            cross_attention_kwargs={"scale": strength},
         ).images[0]
     
     return image, seed
@@ -56,7 +64,6 @@ with gr.Blocks(theme='default', css=css) as app:
                 steps = gr.Slider(label="Sampling steps", value=30, minimum=10, maximum=50, step=1)
                 cfg_scale = gr.Slider(label="CFG Scale", value=7.5, minimum=1, maximum=15, step=0.5)
             with gr.Column():
-                strength = gr.Slider(label="LoRA Strength", value=0.75, minimum=0, maximum=1, step=0.01)
                 seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1)
 
         with gr.Row():
@@ -70,7 +77,7 @@ with gr.Blocks(theme='default', css=css) as app:
 
         generate_button.click(
             generate_image, 
-            inputs=[text_prompt, negative_prompt, steps, cfg_scale, seed, strength], 
+            inputs=[text_prompt, negative_prompt, steps, cfg_scale, seed, strength],
             outputs=[image_output, seed_output]
         )