Create app.py

app.py

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+import gradio as gr
+from keras.models import load_model
+import pickle
+import torch
+import numpy as np
+import pandas as pd
+from utils import test_sentences
+
+model = torch.load('bert_classification(0.87).pt')
+
+# Gradio 인터페이스에서 사용할 함수 정의
+def predict_sentiment(text):
+  logit = test_sentences([text], model)
+  sent = np.argmax(logit)
+
+  classes = {0: "중립", 1:"긍정", 2:"부정"}
+  sentiment = classes[sent]
+
+  return sentiment
+
+title = "🤷‍♀️🤷‍♂️What is the EMOTION of TWEET❔"
+description = "▶트위터 감정 알아보기"
+
+
+tweet = gr.Interface(
+    fn=predict_sentiment,
+    inputs=gr.inputs.Textbox(placeholder="Enter tweet here..."),
+    outputs=gr.outputs.Textbox(label="Sentiment Prediction"),
+    title=title,
+    theme="finlaymacklon/boxy_violet",
+    description=description
+)
+tweet.launch(share=True)