Update app.py

app.py

@@ -6,7 +6,9 @@ import torch
 from diffusers import DiffusionPipeline, FlowMatchEulerDiscreteScheduler, FluxTransformer2DModel, FluxPipeline
 from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5TokenizerFast
 from huggingface_hub import hf_hub_download
+import os
 
+token_hf = os.environ["HF_TOKEN"]
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
@@ -14,10 +16,10 @@ repo_name = "ByteDance/Hyper-SD"
 ckpt_name = "Hyper-FLUX.1-dev-8steps-lora.safetensors"
 hyper_lora = hf_hub_download(repo_name, ckpt_name)
 
-pipe = FluxPipeline.from_pretrained(base_model_id, token="xxx")
+pipe = FluxPipeline.from_pretrained(base_model_id, token=token_hf)
 pipe.load_lora_weights(hf_hub_download(repo_name, ckpt_name))
 pipe.fuse_lora(lora_scale=0.125)
-pipe.to("cuda", dtype=torch.float16)
+pipe.to("cuda", dtype=dtype)
 
 
 # pipe = FluxPipeline.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16).to(device)