| encoding = tokenizer(table, question, return_tensors="pt") | |
| let the model generate an answer autoregressively | |
| outputs = model.generate(**encoding) | |
| decode back to text | |
| predicted_answer = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0] | |
| print(predicted_answer) | |
| 53 | |
| Note that [TapexTokenizer] also supports batched inference. |