| import gradio as gr | |
| from transformers import AutoModelForSequenceClassification | |
| from transformers import AutoTokenizer | |
| model = AutoModelForSequenceClassification.from_pretrained("AlCyede/sarcastic-text_prediction") | |
| tokenizer = AutoTokenizer.from_pretrained("distilbert-base-uncased") | |
| def predict(text): | |
| inputs = tokenizer(text, padding=True, truncation=True, return_tensors="pt") | |
| outputs = model(**inputs) | |
| logits = outputs.logits | |
| predicted_class_id = logits.argmax().item() | |
| predicted_class_prob = logits.softmax(dim=1)[0][predicted_class_id].item() | |
| return f"prediction: {model.config.id2label[predicted_class_id]}\nconfidence: {predicted_class_prob * 100:.02f}%" | |
| demo = gr.Interface(fn=predict, inputs="text", outputs="text") | |
| demo.launch(share=True) |