Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration
+
+model_name = 'ainize/kobart-news'
+
+tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+def summ(txt):
+  input_ids = tokenizer.encode(txt, return_tensors="pt")
+  summary_text_ids = model.generate(
+    input_ids=input_ids,
+    bos_token_id=model.config.bos_token_id,
+    eos_token_id=model.config.eos_token_id,
+    length_penalty=2.0,
+    max_length=142,
+    min_length=56,
+    num_beams=4,
+  )
+  return tokenizer.decode(summary_text_ids[0], skip_special_tokens=True)
+
+interface = gr.Interface(summ, [gr.Textbox(label = 'original text')],
+                        [gr.Textbokx(label = 'summary')])
+
+interface.launch(share = True)