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.gitattributes

@@ -35,3 +35,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 khmer_to_vi_folder/variables/variables.data-00000-of-00001 filter=lfs diff=lfs merge=lfs -text
 khmer_to_vietnamese_fix_final3.keras filter=lfs diff=lfs merge=lfs -text
+translate_khmer_to_vi_fix_final.keras filter=lfs diff=lfs merge=lfs -text

run.py

@@ -0,0 +1,36 @@
+from tokenizers import Tokenizer
+from tensorflow.keras.models import load_model
+from tensorflow.keras.preprocessing.sequence import pad_sequences
+import numpy as np
+# 1. Load từ file tokenizer.json
+src_tokenizer = Tokenizer.from_file("khmer_tokenizer.json")
+tgt_tokenizer = Tokenizer.from_file("vietnamese_tokenizer.json")
+model = load_model("translate_khmer_to_vi_fix_final.keras")
+max_len_src= 963
+max_len_tgt= 268
+model.summary()
+# def translate_sentence(sentence):
+
+#     sentence_ids = src_tokenizer.encode(sentence).ids
+#     sentence_decode_in = tgt_tokenizer.encode("<s>" + sentence).ids
+
+#     # return sentence_ids
+#     x_train = pad_sequences([sentence_ids], maxlen=max_len_src, padding='post')
+#     train_encoder = pad_sequences([sentence_decode_in],maxlen=max_len_tgt-1,padding='post')
+#     output = model.predict([x_train,train_encoder])
+#     # return output
+
+#     predicted_ids = np.argmax(output[0], axis=-1)
+#     # return predicted_ids
+#     # return tgt_tokenizer.decode(output[0]), tgt_tokenizer.decode(output[1])
+#     tokens = tgt_tokenizer.decode(predicted_ids)
+
+#     return tokens
+
+#     # return predicted_ids
+
+
+# khmer_sentence = "លោកនាយករដ្ឋមន្រ្តីទើបតែបានអត្ថាធិប្បាយលើព័ត៌មានមួយចំនួនដែលបានលើកឡើងនៅក្នុងកាសែតអេឡិចត្រូនិក VietNamNet ដែលទាក់ទងនឹង…"
+
+
+# print(translate_sentence(khmer_sentence))

translate_khmer_to_vi_fix_final.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b6b021ff9f6fa2fd952e08d5a0f57e6ea81ef03931c539097e92a174e7aa3b20
+size 162507369