Update app.py

app.py

@@ -1,3 +1,4 @@
+
 import gradio as gr
 import json
 import os
@@ -14,12 +15,9 @@ import tempfile
 import warnings
 import string
 import spaces
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-from transformers import AutoConfig
+from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig
 import torch
 
-
 warnings.filterwarnings("ignore")
 
 # Map Tile Providers with reliable sources
@@ -79,17 +77,25 @@ class SafeGeocoder:
             return None
 
 
-# Replace the model loading section with this:
+# Fixed model loading function
 def load_model():
     global tokenizer, model
     try:
         if model is None:
-            # Special handling for NuExtract tokenizer
+            # First, try to get configuration to check model type
+            config = AutoConfig.from_pretrained(MODEL_NAME, trust_remote_code=True)
+            print(f"Loading model config: {config.__class__.__name__}")
+            
+            # Load tokenizer with appropriate options
             tokenizer = AutoTokenizer.from_pretrained(
                 MODEL_NAME,
-                trust_remote_code=True
+                trust_remote_code=True,
+                use_fast=False  # Try with use_fast=False if the regular tokenizer fails
             )
             
+            print(f"Successfully loaded tokenizer: {tokenizer.__class__.__name__}")
+            
+            # Load the model
             model = AutoModelForCausalLM.from_pretrained(
                 MODEL_NAME,
                 torch_dtype=TORCH_DTYPE,
@@ -119,6 +125,9 @@ def load_model():
         return "⚠️ Modell-Test nicht erfolgreich. Bitte versuchen Sie es erneut."
         
     except Exception as e:
+        import traceback
+        trace = traceback.format_exc()
+        print(f"Error loading model: {e}\n{trace}")
         return f"❌ Fehler beim Laden des Modells: {str(e)}"
 
 @spaces.GPU
@@ -360,8 +369,7 @@ h2 {
     border-top: 1px solid #eaeaea;
 }
 </style>
-"""
-
+""" 
 with gr.Blocks(css=custom_css, title="Daten Strukturieren und Analysieren") as demo:
     gr.HTML("""
     <div style="text-align: center; margin-bottom: 1rem">