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