| import gradio as gr | |
| from transformers import pipeline | |
| # Load your fine-tuned model from local path or Hugging Face Hub | |
| classifier = pipeline("text-classification", model="sm3455/bert-mlm-ft") | |
| def classify_text(text): | |
| result = classifier(text) | |
| label = result[0]['label'] | |
| score = result[0]['score'] | |
| return f"{label} ({score:.2f})" | |
| iface = gr.Interface( | |
| fn=classify_text, | |
| inputs=gr.Textbox(lines=2, placeholder="Enter your text here..."), | |
| outputs="text", | |
| title="My Text Classifier", | |
| description="A demo for my fine-tuned model using Gradio" | |
| ) | |
| iface.launch() | |