Update Mo.py

Mo.py

@@ -196,7 +196,7 @@ class Block(layers.Layer):
         x = self.lo(x)
         return x
 
-class C(tf.keras.Model):
+class CumaLM(tf.keras.Model):
     def __init__(self, vocab_size, max_seq_len, d_model, n_layers, dropout_rate=0.1):
         super().__init__()
         self.token_embedding = layers.Embedding(vocab_size, d_model)
@@ -242,7 +242,7 @@ def masked_perplexity(y_true, y_pred, eps=0.1):
 # 모델 생성 & 컴파일
 # =======================
 with strategy.scope():
-    model = ReLM(vocab_size=vocab_size, max_seq_len=max_len, d_ff=768, n_layers=12)
+    model = CumaLM(vocab_size=vocab_size, max_seq_len=max_len, d_ff=768, n_layers=12)
     dummy_input = tf.zeros((batch_size, max_len), dtype=tf.int32)
     _ = model(dummy_input, training=False)
     model.summary()