Update README.md

README.md

@@ -19,21 +19,15 @@ Example on SST-2 test dataset classification:
 from datasets import load_dataset  
 import numpy as np  
 from sklearn.metrics import accuracy_score  
-
 from keras.preprocessing.text import Tokenizer
 from keras.utils import pad_sequences
 import tensorflow as tf
-
 from huggingface_hub import from_pretrained_keras
 
 from datasets import load_dataset
 sst2 = load_dataset("SetFit/sst2")
 augmented_sst2_dataset = load_dataset("jmamou/augmented-glue-sst2")
 
-oov_token = '<UNK>' # Required only if test is not given 
-pad_type = 'post'
-trunc_type = 'post'
-
 # Tokenize our training data
 tokenizer = Tokenizer(num_words=10000)
 tokenizer.fit_on_texts(augmented_sst2_dataset['train']['sentence'])
@@ -42,7 +36,7 @@ tokenizer.fit_on_texts(augmented_sst2_dataset['train']['sentence'])
 test_sequences = tokenizer.texts_to_sequences(sst2['test']['text'])
 
 # Pad the training sequences
-test_padded = pad_sequences(test_sequences, padding=pad_type, truncating=trunc_type, maxlen=64)
+test_padded = pad_sequences(test_sequences, padding=pad_type = 'post', truncating=trunc_type = 'post', maxlen=64)
 
 reloaded_model = from_pretrained_keras('moshew/distilbilstm-finetuned-sst-2-english')