Update prediction_multilabel.py

prediction_multilabel.py

@@ -10,15 +10,15 @@ from sentence_transformers import util
 torch.manual_seed(1)
 
 # Load datasets
-df_inmemory = pd.read_csv('labeled.csv') # labeled text extracted from 230 CSR GRI reports, 150 International companies, 2017-2021 period
-df_paragraph = pd.read_csv('prediction_demo.csv') # paragraphs to predict the label, extracted from 1.2k CSR reports, 150 German PLC companies, 2010-2021 period, 645k paragraphs)
+df_inmemory = pd.read_csv('raw_data/labeled.csv') # labeled text extracted from 230 CSR GRI reports, 150 International companies, 2017-2021 period
+df_paragraph = pd.read_csv('raw_data/prediction_demo.csv') # paragraphs to predict the label, extracted from 1.2k CSR reports, 150 German PLC companies, 2010-2021 period, 645k paragraphs)
 
 # Load stored embeddings
-with open('embeddings_prediction.pkl', "rb") as f:
+with open('embeddings/embeddings_prediction.pkl', "rb") as f:
     stored_data = pickle.load(f)
     pred_embeddings = stored_data['parg_embeddings']
 
-with open('embeddings_labeled.pkl', "rb") as f:
+with open('embeddings/embeddings_labeled.pkl', "rb") as f:
     stored_data = pickle.load(f)
     embeddings = stored_data['sent_embeddings']