Update app.py

app.py

@@ -5,11 +5,11 @@ from transformers import T5Tokenizer, T5ForConditionalGeneration
 def generate_text(input_text):
     # Load pre-trained model and tokenizer
     model_name = 'kurry/t5_small_finetuned'
-    model = T5ForConditionalGeneration.from_pretrained(model_name, map_location=torch.device('cpu'))
+    model = T5ForConditionalGeneration.from_pretrained(model_name).to('cpu')
     tokenizer = T5Tokenizer.from_pretrained(model_name)
 
     # Generate summary
-    inputs = tokenizer.encode("summarize: " + input_text, return_tensors="pt", truncation=True)
+    inputs = tokenizer.encode("summarize: " + input_text, return_tensors="pt", truncation=True).to('cpu')
     outputs = model.generate(inputs)
     return tokenizer.decode(outputs[0], skip_special_tokens=True)