| import gradio as gr | |
| from transformers import pipeline | |
| # Load the fine-tuned model from Hugging Face Hub | |
| classifier = pipeline("text-classification", model="Emanai/my-finetuned-bert2") | |
| def classify_text(text): | |
| result=classifier(text) | |
| return '{} - {}'.format(result[0]['score'], result[0]['label']) | |
| # Create a simple Gradio interface | |
| iface = gr.Interface(fn=classify_text, inputs="text", outputs="label") | |
| # Launch the Gradio app | |
| iface.launch() |