update

app.py

@@ -93,7 +93,7 @@ def change_model_fn(model_name: str) -> None:
             # variant="fp16",
             torch_dtype=torch.bfloat16,
             feature_extractor=None
-        )
+        ).to(device)
         pipeline = ConceptrolIPAdapterPlusXL(pipe, "", adapter_name, device, num_tokens=16)
         globals()["pipeline"] = pipeline
     

ip_adapter/custom_pipelines.py

@@ -408,7 +408,7 @@ class StableDiffusionXLCustomPipeline(StableDiffusionXLPipeline):
         if not output_type == "latent":
             # make sure the VAE is in float32 mode, as it overflows in float16
             needs_upcasting = (
-                self.vae.dtype == torch.bfloat16 and self.vae.config.force_upcast
+                self.vae.dtype == torch.float16 and self.vae.config.force_upcast
             )
 
             if needs_upcasting:
@@ -423,7 +423,7 @@ class StableDiffusionXLCustomPipeline(StableDiffusionXLPipeline):
 
             # cast back to fp16 if needed
             if needs_upcasting:
-                self.vae.to(dtype=torch.bfloat16)
+                self.vae.to(dtype=torch.float16)
         else:
             image = latents