resolving issues

app.py

@@ -3,6 +3,7 @@ from PIL import Image
 import torch
 from transformers import Qwen2VLForConditionalGeneration, AutoProcessor, AutoModelForImageToText
 from colpali_engine.models import ColPali, ColPaliProcessor
+from huggingface_hub import login
 import os
 
 # Set device for computation
@@ -11,26 +12,29 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 # Get Hugging Face token from environment variables
 hf_token = os.getenv('HF_TOKEN')
 
-# Load the processor and image-to-text model directly using Hugging Face token
+# Log in to Hugging Face Hub (this will authenticate globally)
+login(token=hf_token)
+
+# Load the processor and image-to-text model directly
 try:
-    processor_img_to_text = AutoProcessor.from_pretrained("google/paligemma-3b-mix-448", use_auth_token=hf_token)
-    model_img_to_text = AutoModelForImageToText.from_pretrained("google/paligemma-3b-mix-448", use_auth_token=hf_token).to(device)
+    processor_img_to_text = AutoProcessor.from_pretrained("google/paligemma-3b-mix-448")
+    model_img_to_text = AutoModelForImageToText.from_pretrained("google/paligemma-3b-mix-448").to(device)
 except Exception as e:
     st.error(f"Error loading image-to-text model: {e}")
     st.stop()
 
 # Load ColPali model with Hugging Face token
 try:
-    model_colpali = ColPali.from_pretrained("vidore/colpali-v1.2", torch_dtype=torch.bfloat16, use_auth_token=hf_token).to(device)
-    processor_colpali = ColPaliProcessor.from_pretrained("google/paligemma-3b-mix-448", use_auth_token=hf_token)
+    model_colpali = ColPali.from_pretrained("vidore/colpali-v1.2", torch_dtype=torch.bfloat16).to(device)
+    processor_colpali = ColPaliProcessor.from_pretrained("google/paligemma-3b-mix-448")
 except Exception as e:
     st.error(f"Error loading ColPali model or processor: {e}")
     st.stop()
 
-# Load Qwen model with Hugging Face token
+# Load Qwen model
 try:
-    model_qwen = Qwen2VLForConditionalGeneration.from_pretrained("Qwen/Qwen2-VL-7B-Instruct", use_auth_token=hf_token).to(device)
-    processor_qwen = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-7B-Instruct", use_auth_token=hf_token)
+    model_qwen = Qwen2VLForConditionalGeneration.from_pretrained("Qwen/Qwen2-VL-7B-Instruct").to(device)
+    processor_qwen = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-7B-Instruct")
 except Exception as e:
     st.error(f"Error loading Qwen model or processor: {e}")
     st.stop()