Update app.py

app.py

@@ -28,12 +28,16 @@ def load_model(model_name):
     model_path = models[model_name]
     if torch.cuda.is_available():
         torch.cuda.max_memory_allocated(device=device)
-        pipe = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
+        pipe = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16, variant="fp16")
         pipe.enable_xformers_memory_efficient_attention()
     else:
-        pipe = DiffusionPipeline.from_pretrained(model_path, use_safetensors=True)
+        pipe = DiffusionPipeline.from_pretrained(model_path)
     pipe = pipe.to(device)
     
+    # Disable NSFW filters if the pipeline supports it
+    if hasattr(pipe, 'safety_checker'):
+        pipe.safety_checker = None
+    
     pipelines[model_name] = pipe
     return pipe
 
@@ -49,13 +53,13 @@ def infer(model_name, prompt, negative_prompt, seed, randomize_seed, width, heig
     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
+        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