Update app.py

app.py

@@ -1,19 +1,9 @@
-from transformers import AutoImageProcessor, AutoModelForImageClassification
-import torch
-from datasets import load_dataset
+import transformers
+from transformers import pipeline
 
-dataset = load_dataset("competitions/aiornot")
-image = dataset["test"][0]["image"]
-
-processor = AutoImageProcessor.from_pretrained("microsoft/resnet-50")
-model = AutoModelForImageClassification.from_pretrained("arnolfokam/ai-generated-image-detector", trust_remote_code=True)
-
-inputs = processor(image, return_tensors="pt")
-
-with torch.no_grad():
-    logits = model(**inputs).logits
-
-# model predicts one of the 2 classes
-predicted_label = logits.argmax(-1).item()
-print(model.config.id2label[predicted_label])
+unmasker = pipeline('fill-mask', model='bert-large-uncased')
+user_input = input("Enter a sentence with a masked word: ")
+results = unmasker(user_input)
 
+for result in results:
+    print(result['sequence'])