| import gradio as gr | |
| from transformers import pipeline | |
| classifier = pipeline("sentiment-analysis", model="kkPriyanka/cls_distilbert_model") | |
| def text_classification(text): | |
| result= classifier(text) | |
| sentiment_label = result[0]['label'] | |
| sentiment_score = result[0]['score'] | |
| formatted_output = f"This sentiment is {sentiment_label} with the probability {sentiment_score*100:.2f}%" | |
| return formatted_output | |
| examples=["This is wonderful movie!", "The movie was really bad; I didn't like it."] | |
| io = gr.Interface(fn=text_classification, | |
| inputs= gr.Textbox(lines=2, label="Text", placeholder="Enter title here..."), | |
| outputs=gr.Textbox(lines=2, label="Text Classification Result"), | |
| title="Text Classification", | |
| description="Enter a text and see the text classification result!", | |
| examples=examples) | |
| io.launch(inline=False, share=True) |