Update app.py

app.py

@@ -1,3 +1,4 @@
+import os
 import gradio as gr
 import numpy as np
 import random
@@ -10,10 +11,12 @@ from live_preview_helpers import calculate_shift, retrieve_timesteps, flux_pipe_
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
+token = os.environ.get("HF_TOKEN")
+
 taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
 good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=dtype).to(device)
-pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=taef1).to(device)
-#pipe.load_lora_weights("MegaTronX/MetartLoRA", weight_name="MetartLoRA.safetensors")
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=taef1, use_auth_token=token).to(device)
+pipe.load_lora_weights("MegaTronX/MetartLoRA", weight_name="MetartLoRA.safetensors")
 torch.cuda.empty_cache()
 
 MAX_SEED = np.iinfo(np.int32).max