Create new file

app.py

@@ -0,0 +1,28 @@
+from transformers import T5Tokenizer, T5Model, T5ForConditionalGeneration
+
+tokenizer_t5 = T5Tokenizer.from_pretrained("panggi/t5-base-indonesian-summarization-cased")
+model_t5 = T5ForConditionalGeneration.from_pretrained("panggi/t5-base-indonesian-summarization-cased")
+
+def summ_t5(text):
+  input_ids = tokenizer.encode(text, return_tensors='pt')
+  summary_ids = model_.generate(input_ids,
+              max_length=100, 
+              num_beams=2,
+              repetition_penalty=2.5, 
+              length_penalty=1.0, 
+              early_stopping=True,
+              no_repeat_ngram_size=2,
+              use_cache=True)
+  summary_text = tokenizer_t5.decode(summary_ids[0], skip_special_tokens=True)
+  return summary_text
+  
+sentiment_demo = gr.Interface(
+    fn=summ_t5,
+    inputs="text",
+    outputs="text")
+
+if __name__ == "__main__":
+    Parallel(summ_demo,
+    inputs=gr.Textbox(lines=10, label="Input Text", placeholder="Enter article here..."),
+    title="Summary of Summarizer - Indonesia",
+    examples=examples).launch()