Update app.py

app.py

@@ -5,7 +5,7 @@ import warnings
 warnings.filterwarnings('ignore')
 import re, flair, random, time
 from bnlp import BasicTokenizer
-from flair.data import Corpus
+from flair.data import Corpus, Sentence
 from flair.datasets import ColumnCorpus
 #from flair.embeddings import TransformerWordEmbeddings
 from flair.models import SequenceTagger
@@ -37,8 +37,9 @@ if choice == 'Text Input':
         # columns = {0: 'text'}
         # corpus: Corpus = ColumnCorpus('bengali_pos/', columns, train_file='train.txt', test_file='test.txt', dev_file='valid.txt')
         # '''
+        sentence = Sentence(input_data)
         model = load_model('best-model-002.pt')
-        print(model.predict(input_data))
+        print(model.predict(sentence))
         #print(input_data.to_tagged_string())
         #result_mean = model.evaluate(corpus.test, gold_label_type='pos',mini_batch_size=32, out_path=f"pred_pos.txt")