Create app.py

app.py

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+from transformers import AutoModelForMaskedLM , AutoTokenizer
+import torch
+model_path="bert-large-uncased"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+# load Prompting class
+from prompt import Prompting
+prompting= Prompting(model=model_path)
+prompt= ". Because it was "+ prompting.tokenizer.mask_token +"."
+
+def predict(text):
+  THRESHOLD = prompting.compute_tokens_prob(prompt, token_list1=["good"], token_list2= ["bad"])[0].item()
+  res=prompting.compute_tokens_prob(text+prompt, token_list1=["good"], token_list2= ["bad"])
+  if res[0] > THRESHOLD:
+    return {"POSITIVE":res[0]}
+  return {"NEGATIVE":res[0]}
+   
+ 
+