fix issues with model loading

app.py

@@ -10,13 +10,20 @@ def load_model():
     global _classifier
     if _classifier is None:
         try:
+            # Try loading with trust_remote_code for better compatibility
             _classifier = pipeline(
                 "text-classification",
                 model="YosefA/adfluence-intent-model",
-                return_all_scores=True
+                return_all_scores=True,
+                trust_remote_code=True
             )
+            print("Model loaded successfully!")
         except Exception as e:
-            print(f"Error loading model: {e}")
+            print(f"Error loading model YosefA/adfluence-intent-model: {e}")
+            print("Please verify that:")
+            print("1. The model name is correct")
+            print("2. The model exists and is public")
+            print("3. You have internet connection")
             return None
     return _classifier
 

requirements.txt

@@ -2,4 +2,6 @@ gradio==4.44.0
 transformers==4.36.0
 torch==2.1.0
 tokenizers==0.15.0
-huggingface_hub==0.19.4 
+huggingface_hub==0.19.4
+numpy<2.0.0
+requests==2.31.0 

test_model.py

@@ -0,0 +1,77 @@
+#!/usr/bin/env python3
+"""
+Test script to verify if the Hugging Face model exists and can be loaded.
+Run this to debug model loading issues.
+"""
+
+from transformers import pipeline
+import requests
+
+def test_model_exists(model_name):
+    """Test if model exists on Hugging Face"""
+    url = f"https://huggingface.co/api/models/{model_name}"
+    try:
+        response = requests.get(url)
+        if response.status_code == 200:
+            print(f"✅ Model {model_name} exists on Hugging Face")
+            model_info = response.json()
+            print(f"   Pipeline tag: {model_info.get('pipeline_tag', 'Unknown')}")
+            print(f"   Downloads: {model_info.get('downloads', 'Unknown')}")
+            return True
+        elif response.status_code == 404:
+            print(f"❌ Model {model_name} not found on Hugging Face")
+            return False
+        else:
+            print(f"⚠️  Unexpected response: {response.status_code}")
+            return False
+    except Exception as e:
+        print(f"❌ Error checking model: {e}")
+        return False
+
+def test_model_loading(model_name):
+    """Test loading the model with transformers"""
+    try:
+        print(f"\n🔄 Attempting to load model: {model_name}")
+        classifier = pipeline(
+            "text-classification",
+            model=model_name,
+            return_all_scores=True,
+            trust_remote_code=True
+        )
+        print("✅ Model loaded successfully!")
+        
+        # Test classification
+        test_text = "This product looks amazing!"
+        result = classifier(test_text)
+        print(f"✅ Test classification successful:")
+        print(f"   Input: '{test_text}'")
+        print(f"   Output: {result}")
+        
+        return True
+        
+    except Exception as e:
+        print(f"❌ Error loading model: {e}")
+        return False
+
+def main():
+    model_name = "YosefA/adfluence-intent-model"
+    
+    print(f"🧪 Testing model: {model_name}")
+    print("=" * 50)
+    
+    # Test 1: Check if model exists
+    exists = test_model_exists(model_name)
+    
+    if exists:
+        # Test 2: Try loading the model
+        test_model_loading(model_name)
+    else:
+        print("\n💡 Suggestions:")
+        print("1. Check if the model name is spelled correctly")
+        print("2. Verify the model is public (not private)")
+        print("3. Check if you need to be logged in to access it")
+        print("4. Try searching for similar models:")
+        print("   https://huggingface.co/models?search=intent+classification")
+
+if __name__ == "__main__":
+    main()