Update app_merged.py

app_merged.py

@@ -166,15 +166,22 @@ unet = UNet2DConditionModel.from_pretrained(sd15_name, subfolder="unet")
 
 
 
-fill_pipe = FluxFillPipeline.from_single_file(
-    "https://huggingface.co/SporkySporkness/FLUX.1-Fill-dev-GGUF/flux1-fill-dev-fp16-Q5_0-GGUF.gguf", 
-    text_encoder= text_encoder,
-    text_encoder_2 = t5_path,
-    ignore_mismatched_sizes=True,
-    low_cpu_mem_usage=False,
-    torch_dtype=torch.bfloat16
-).to("cuda")
+# fill_pipe = FluxFillPipeline.from_single_file(
+#     "https://huggingface.co/SporkySporkness/FLUX.1-Fill-dev-GGUF/flux1-fill-dev-fp16-Q5_0-GGUF.gguf", 
+#     text_encoder= text_encoder,
+#     text_encoder_2 = t5_path,
+#     ignore_mismatched_sizes=True,
+#     low_cpu_mem_usage=False,
+#     torch_dtype=torch.bfloat16
+# ).to("cuda")
+
+from diffusers import FluxTransformer2DModel, FluxFillPipeline
+from transformers import T5EncoderModel
+import torch
 
+transformer = FluxTransformer2DModel.from_pretrained("AlekseyCalvin/FluxFillDev_fp8_Diffusers", subfolder="transformer", torch_dtype=torch.bfloat16).to("cuda")
+text_encoder_2 = T5EncoderModel.from_pretrained("AlekseyCalvin/FluxFillDev_fp8_Diffusers", subfolder="text_encoder_2", torch_dtype=torch.bfloat16).to("cuda")
+fill_pipe = FluxFillPipeline.from_pretrained("black-forest-labs/FLUX.1-Fill-dev", transformer=transformer, text_encoder_2=text_encoder_2, torch_dtype=torch.bfloat16).to("cuda")
 
 
 try: