add code sample on readme

README.md

@@ -16,3 +16,41 @@ This model is fine-tuned based on the original [BERT2BERT Indonesian Summarizati
 - **Task**: Summarization
 
 This model was fine-tuned using the [Liputan6_ID](https://huggingface.co/datasets/fajrikoto/id_liputan6) dataset, which contains Indonesian news articles. The model is optimized for summarizing domain-specific texts from the Liputan6 dataset.
+
+## Code Sample
+
+```python
+from transformers import BertTokenizer, EncoderDecoderModel
+
+tokenizer = BertTokenizer.from_pretrained("rowjak/bert-indonesian-news-summarization")
+tokenizer.bos_token = tokenizer.cls_token
+tokenizer.eos_token = tokenizer.sep_token
+model = EncoderDecoderModel.from_pretrained("rowjak/bert-indonesian-news-summarization")
+
+# 
+ARTICLE = ""
+
+# generate summary
+input_ids = tokenizer.encode(ARTICLE, return_tensors='pt')
+summary_ids = model.generate(input_ids,
+            max_length=150, 
+            num_beams=10,
+            repetition_penalty=2.5, 
+            length_penalty=1.0, 
+            early_stopping=True,
+            no_repeat_ngram_size=2,
+            use_cache=True,
+            do_sample = True,
+            temperature = 0.8,
+            top_k = 50,
+            top_p = 0.95)
+
+summary_text = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+print(summary_text)
+```
+
+Output:
+
+```
+---
+```