Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import torch
+
+id2label = {0: "NEGATIVE", 1: "POSITIVE"}
+label2id = {"NEGATIVE": 0, "POSITIVE": 1}
+
+# 导入在 HuggingFace 我们刚刚训练好而且上传成功的模型 chjun/my_awesome_model
+classifier = pipeline("sentiment-analysis", model="chjun/my_awesome_model")
+
+# inputs：输入文本
+def predict(inputs):
+    label_score = classifier(inputs)
+    scaled = 0
+    if label_score[0]["label"] == "NEGATIVE":
+      scaled = 1 - label_score[0]["score"]
+    else:
+      scaled = label_score[0]["score"]
+
+    # 解码返回值得到输出
+    return round(scaled * 5)
+
+with gr.Blocks() as demo:
+    review = gr.Textbox(label="用户评论。注：此模型只使用了英文数据 Finetune")
+    output = gr.Textbox(label="颗星")
+    submit_btn = gr.Button("提交")
+    submit_btn.click(fn=predict, inputs=review, outputs=output)    
+
+demo.launch(debug=True)