feat(app.py): less code

app.py

@@ -4,25 +4,21 @@ import gradio as gr
 from huggingface_hub import login
 import os
 login(os.environ["HF_Token"])
-model = AutoModel.from_pretrained(
-    "minskiter/resume-token-classification",
-    use_auth_token=True,
-    trust_remote_code=True
-)
-tokenizer = AutoTokenizer.from_pretrained(
-    "hfl/chinese-bert-wwm"
-)
 ner_predictor = pipeline(
     task="nerpipe",
-    model=model, 
-    config=model.config,
-    tokenizer=tokenizer,
+    model="minskiter/resume-token-classification",
     device="cpu",
-    trust_remote_code=True
+    trust_remote_code=True,
+    use_auth_token=True
 )
 
 def ner_predictor_gradio(input):
-    return ner_predictor(input)
+    entities = ner_predictor(input)
+    return {"text":input, "entities":entities}
 
-demo = gr.Interface(fn=ner_predictor_gradio, inputs="text", outputs="text")
+demo = gr.Interface(
+    fn=ner_predictor_gradio, 
+    inputs=gr.Textbox(lines=5, label="输入你的简历"), 
+    outputs=gr.HighlightedText(label="简历识别结果"),
+)
 demo.launch()