Create app.py

app.py

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+import gradio as gr
+
+from transformers import PreTrainedTokenizerFast, BartForConditionalGeneration
+# from transformers import로 시작하는 import 문을 보면
+# 많은 경우 AutoTokenizer, AutoModel
+# tokenizer = AutoTokenizer.from_pretrained("model 이름 어쩌고 저쩌고")
+# PreTrainedTokenizerFast : https://huggingface.co/docs/transformers/main_classes/tokenizer
+# BART는 encoder-decoder 모델의 예시
+
+model_name = "ainize/kobart-news"
+tokenizer = PreTrainedTokenizerFast.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+# 원문을 받아서 요약문을 반환
+def summ(txt):
+  input_ids = tokenizer.encode(input_text, 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.Textbox(label="summary")])
+
+interface.launch(share=True)