Add torch_dtype

app.py

@@ -37,9 +37,9 @@ else:
         msg = "Invalid LoRA checkpoint."
         raise ValueError(msg)
 
-    pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev").to(
-        DEVICE
-    )
+    pipe = FluxFillPipeline.from_pretrained(
+        "black-forest-labs/FLUX.1-Fill-dev", torch_dtype=torch.bfloat16
+    ).to(DEVICE)
     FluxFillPipeline.load_lora_into_transformer(
         state_dict=state_dict,
         network_alphas=network_alphas,