Update app.py

app.py

@@ -3,12 +3,12 @@ import gradio as gr
 import pandas as pd
 import tempfile
 import itertools
-# import required packages
+  # import required packages
 import torch
+import pandas as pd
 import numpy as np
 from numpy import dot
-from numpy.linalg import norm
-import transformers
+from numpy.linalg import norm, multi_dot
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer
 
 # compute dot product of inputs
@@ -26,11 +26,11 @@ def gr_cosine_similarity(sentence1, sentence2):
           return {k: v[idx] for k, v in self.tokenized_texts.items()}
 
   # load tokenizer and model, create trainer
-  model_name = "j-hartmann/emotion-english-distilroberta-base" 
-  tokenizer = AutoTokenizer.from_pretrained(model_name) 
+  model_name = "j-hartmann/emotion-english-distilroberta-base"
+  tokenizer = AutoTokenizer.from_pretrained(model_name)
   model = AutoModelForSequenceClassification.from_pretrained(model_name)
   trainer = Trainer(model=model)  
-
+    
   # sentences in list
   lines_s = [sentence1, sentence2]
   print(type(sentence1), type(sentence2))
@@ -91,6 +91,8 @@ def gr_cosine_similarity(sentence1, sentence2):
 
   # return dataframe for space output
   return  df, cosine_similarity
+  
+ 
 
 gr.Interface(gr_cosine_similarity,
                    [