Update app.py

app.py

@@ -1,22 +1,18 @@
+!pip install transformers
+
 # imports
 import gradio as gr
 import pandas as pd
 import tempfile
 import itertools
   # import required packages
-#import torch
-import pandas as pd
+import torch
+
 import numpy as np
 from numpy import dot
 from numpy.linalg import norm, multi_dot
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, Trainer
 
-# load tokenizer and model, create trainer
-model_name = "j-hartmann/emotion-english-distilroberta-base"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-trainer = Trainer(model=model)  
-
 # compute dot product of inputs
 # summary function - test for single gradio function interfrace
 def gr_cosine_similarity(sentence1, sentence2):
@@ -31,6 +27,13 @@ def gr_cosine_similarity(sentence1, sentence2):
       def __getitem__(self, idx):
           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 = AutoModelForSequenceClassification.from_pretrained(model_name)
+  trainer = Trainer(model=model)  
+
+    
   # sentences in list
   lines_s = [sentence1, sentence2]
   print(type(sentence1), type(sentence2))