put download model up top

model.py

@@ -1,3 +1,22 @@
+# Importing libraries
+from nltk.corpus import wordnet
+import nltk
+import transformers
+import pandas as pd
+import json
+import random
+import torch
+
+device='cpu'
+
+# Declare the (trained) model that will be used
+classifier = transformers.pipeline("zero-shot-classification", model="simple_trained_wsd_pipeline", device=device)
+
+import spacy
+# Part Of Speech tagging (POS tagging)
+nlp = spacy.load("en_core_web_sm")
+
+
 def model(passage, level):
   # pip install spacy
   # pip install transformers
@@ -7,16 +26,6 @@ def model(passage, level):
   # pip install spacy-download
   # pip install nltk
 
-  # Importing libraries
-  from nltk.corpus import wordnet
-  import spacy
-  import nltk
-  import transformers
-  import pandas as pd
-  import json
-  import random
-  import torch
-
   nltk.download('wordnet')
   nltk.download('omw-1.4')
 
@@ -48,9 +57,6 @@ def model(passage, level):
   else:
     txt = txt
 
-  # Part Of Speech tagging (POS tagging)
-  nlp = spacy.load("en_core_web_sm")
-
   text_dict = {}
   for n in txt:
     n = n.strip()
@@ -140,10 +146,7 @@ def model(passage, level):
   # if torch.cuda.is_available():
   #     device=0
   # else:
-  device='cpu'
 
-  # Declare the (trained) model that will be used
-  classifier = transformers.pipeline("zero-shot-classification", model="simple_trained_wsd_pipeline", device=device)
 
   # Process Python dictionary, def_filtered
   correct_def = {}