Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transforemrs import PretrainedTokenizerFast, BartForCondtionalGeneration
+
+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, # BOS는 Beginning of Sentence
+    eos_token_id=model.config.eos_token_id, # EOS는 End of Sentence
+    length_penalty=2.0, # 요약을 얼마나 짧게 할지
+    max_length=142, # 최대 142 토큰으로 요약
+    min_length=56,  # 최소 56 토큰보다는 더 나옴
+    num_beams=4    # beam search
+  )
+  return tokenizer.decode(summary_text_ids[0], skip_special_tokens=True)
+
+interface = gr.Interface(summ,
+                        [gr.Textbox(label="original text")], # gradio를 이용해서 gui
+                        [gr.Textbox(label="summary")])
+
+interface.launch() # share가 True일 경우, link가 하나 나옴