Update app.py

app.py

@@ -88,10 +88,14 @@ scheduler = ReduceLROnPlateau(optimizer, mode='min', factor=0.5, patience=3, ver
 # Load SentenceTransformer model
 clip_model = SentenceTransformer('sentence-transformers/clip-ViT-B-32-multilingual-v1').to(device)
 
+# Load GPT-Neo and set padding token
 model_name = "EleutherAI/gpt-neo-1.3B"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
+if tokenizer.pad_token is None:
+    tokenizer.pad_token = tokenizer.eos_token  # Set pad_token to eos_token
 model_gptneo = AutoModelForCausalLM.from_pretrained(model_name).to(device)
 
+
 def generate_description(image):
     image_resnet = data_transforms(image).unsqueeze(0).to(device)
 
@@ -123,13 +127,14 @@ def generate_description(image):
         top_p=0.9,
         repetition_penalty=1.2,
         do_sample=True,
-        pad_token_id=tokenizer.eos_token_id
+        pad_token_id=tokenizer.pad_token_id
     )
 
     description_text = tokenizer.decode(output[0], skip_special_tokens=True)
 
     return predicted_style, predicted_artist, description_text
 
+
 # Gradio interface
 def gradio_interface(image):
     if image is None: