Update app.py

app.py

@@ -3,14 +3,13 @@ import numpy as np
 import random
 import spaces
 import torch
-from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler, FluxTransformer2DModel
+from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler, FluxTransformer2DModel, FluxPipeline
 from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-transformer = FluxTransformer2DModel.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=dtype)
-pipe = FluxPipeline.from_pretrained("sayakpaul/FLUX.1-merged", transformer=transformer, torch_dtype=torch.bfloat16).to(device)
+pipe = FluxPipeline.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16).to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048