| from transformers import AutoTokenizer, AutoModel | |
| import gradio as gr | |
| def predict(input_text): | |
| inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True, max_length=512) | |
| with torch.no_grad(): | |
| outputs = model(**inputs) | |
| predictions = torch.softmax(outputs.logits, dim=-1) | |
| predicted_class = predictions.argmax().item() | |
| return f"Predicted class: {predicted_class}" | |
| iface = gr.Interface(fn=predict, | |
| inputs=gr.inputs.Textbox(lines=2, placeholder="Type your text here..."), | |
| outputs="text", | |
| title="My Model Demo", | |
| description="Enter some text to see the model prediction.") | |
| iface.launch() |