However, note that inference is different depending on whether or not the setup is conversational. In a non-conversational set-up, inference can be done in parallel on all table-question pairs of a batch. Here's an example of that:
```py
from transformers import TapasTokenizer, TapasForQuestionAnswering
import pandas as pd
model_name = "google/tapas-base-finetuned-wtq"
model = TapasForQuestionAnswering.from_pretrained(model_name)
tokenizer = TapasTokenizer.from_pretrained(model_name)
data = {"Actors": ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"], "Number of movies": ["87", "53", "69"]}
queries = [
...     "What is the name of the first actor?",
...     "How many movies has George Clooney played in?",
...     "What is the total number of movies?",
... ]
table = pd.DataFrame.from_dict(data)
