Update helper.py

helper.py

@@ -6,6 +6,7 @@ import keras
 import os
 import warnings
 import tempfile
+import torch
 import tensorflow as tf
 from transformers import BertTokenizer, TFBertModel
 from string import punctuation
@@ -31,7 +32,13 @@ stop_words = set(stopwords_df['stopword'].astype(str).tolist())
 
 # Load tokenizer & model
 tokenizer = BertTokenizer.from_pretrained("data")
-bert_model = TFBertModel.from_pretrained("data")
+bert_model = BertModel.from_pretrained("data")
+
+# Di fungsi predict_emotion:
+with torch.no_grad():
+    tokens = tokenizer(cleaned, return_tensors="pt", padding='max_length', truncation=True, max_length=MAX_LENGTH)
+    outputs = bert_model(**tokens)
+    embeddings = outputs.last_hidden_state.numpy().astype(np.float32)
 lstm_model = keras.models.load_model(os.path.join(model_path, 'indobert_lstm_model.keras'))
 
 # --- Preprocessing Functions ---