swap pipeline

inference.py

@@ -165,6 +165,6 @@ class DiffusionInference:
             random_seed = random.randint(0, 3999999999)  # Max 32-bit integer
             generator = torch.Generator(device="cuda").manual_seed(random_seed)
             print(f"Using random seed: {random_seed}")
-        pipeline = AutoPipelineForText2Image.from_pretrained(model_name, generator=generator, torch_dtype=torch.float16).to("cuda")
+        pipeline = DiffusionPipeline.from_pretrained(model_name, generator=generator, torch_dtype=torch.float16).to("cuda")
         image = pipeline(**kwargs).images[0]
         return image