Update app.py

app.py

@@ -3,15 +3,13 @@ import numpy as np
 import random
 import spaces
 import torch
-import os
 from diffusers import  DiffusionPipeline, FlowMatchEulerDiscreteScheduler
 from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
 
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
-HF_TOKEN = os.environ["HF_TOKEN"]
 
-pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, token=HF_TOKEN).to(device)
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16).to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048