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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) |