Update app.py

app.py

@@ -9,13 +9,13 @@ from datasets import load_dataset
 import os
 
 #Import corpus embeddings
-corpus_ger = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_ger', token=str(os.environ['private_token'])))['train']
-corpus_eng = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_eng', token=str(os.environ['private_token'])))['train']
-corpus_fr = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_fr', token=str(os.environ['private_token'])))['train']
+corpus_ger = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_ger', token=str(os.environ['private_token']))['train'])
+corpus_eng = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_eng', token=str(os.environ['private_token']))['train'])
+corpus_fr = pd.DataFrame(load_dataset('ECLASS-Standard/eclass_properties_fr', token=str(os.environ['private_token']))['train'])
 #Import models
-model_ger = SentenceTransformer('ECLASS-Standard/gbert-base-eclass') #, token=str(os.environ['private_token'])
-model_eng = SentenceTransformer('ECLASS-Standard/mboth-distil-eng-quora-sentence') #, token=str(os.environ['private_token'])
-model_fr = SentenceTransformer('ECLASS-Standard/Sahajtomar-french_semantic') #, token=str(os.environ['private_token'])
+model_ger = SentenceTransformer('ECLASS-Standard/gbert-base-eclass', token=str(os.environ['private_token'])
+model_eng = SentenceTransformer('ECLASS-Standard/mboth-distil-eng-quora-sentence', token=str(os.environ['private_token'])
+model_fr = SentenceTransformer('ECLASS-Standard/Sahajtomar-french_semantic', token=str(os.environ['private_token'])
 
 #Definition of search function
 def predict(name, description, language, classCode='nofilter', top_k=10):