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| import gradio as gr | |
| from transformers import pipeline | |
| # 加载 Hugging Face 的预训练文本分类模型 | |
| classifier = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english") | |
| # 定义预测函数 | |
| def predict(text): | |
| result = classifier(text) | |
| return f"Sentiment: {result[0]['label']} (Confidence: {result[0]['score']:.4f})" | |
| # 创建 Gradio 界面 | |
| iface = gr.Interface( | |
| fn=predict, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter text to classify..."), | |
| outputs="text", | |
| title="Text Sentiment Classifier", | |
| description="Enter a sentence to predict its sentiment using a pre-trained model." | |
| ) | |
| # 启动 Gradio 应用 | |
| iface.launch() |