Update app.py

app.py

@@ -1,18 +1,21 @@
 from transformers import AutoModelForMaskedLM , AutoTokenizer
 import torch
-model_path="bert-large-uncased"
+model_path="bert-base-multilingual-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]}
-   
- 
-  
+    return {"POSITIVE":res[0].item()-THRESHOLD}
+  return {"NEGATIVE":THRESHOLD-res[1].item()}
+
+
+
+import gradio as gr
+iface = gr.Interface(fn=predict, inputs=["text"], outputs=["label"]).launch()