Update app.py

app.py

@@ -1,11 +1,17 @@
 import gradio 
+from huggingface_hub import login
+import os
+
+hf_token = os.environ.get("HF_TOKEN")
+login(token=hf_token)
+
 from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL
 from diffusers.utils import load_image
 from PIL import Image
 import torch
 import numpy as np
 import cv2
-import os 
+
 
 controlnet = ControlNetModel.from_pretrained(
     "diffusers/controlnet-canny-sdxl-1.0",
@@ -18,6 +24,12 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     vae=vae,
     torch_dtype=torch.float16,
 )
+
+custom_model = "fffiloni/eugene_jour_general"
+
+# This is where you load your trained weights
+pipe.load_lora_weights(custom_model, use_auth_token=True)
+#pipe.to("cuda")
 pipe.enable_model_cpu_offload()
 
 def infer(image_in):
@@ -28,8 +40,6 @@ def infer(image_in):
 
     controlnet_conditioning_scale = 0.5  # recommended for good generalization
 
-
-
     image = np.array(image)
     image = cv2.Canny(image, 100, 200)
     image = image[:, :, None]