| from transformers import pipeline | |
| import pandas as pd | |
| # prepare table + question | |
| data = {"Actors": ["Brad Pitt", "Leonardo Di Caprio", | |
| "George Clooney"], "Number of movies": ["87", "53", "69"]} | |
| # table = pd.DataFrame.from_dict(data) | |
| query = "how many movies does Leonardo Di Caprio have?" | |
| # data = { | |
| # "year": [1896, 1900, 1904, 2004, 2008, 2012], | |
| # "city": ["athens", "paris", "st. louis", "athens", "beijing", "london"] | |
| # } | |
| tablle = pd.DataFrame.from_dict(data) | |
| # query = "when london had the olympics game?" | |
| # pipeline model | |
| # Note: you must to install torch-scatter first. | |
| tqa = pipeline(task="table-question-answering", | |
| model="google/tapas-large-finetuned-wtq") | |
| # result | |
| result = tqa(table=tablle, query=query) | |
| print(f"Result: {result}") | |
| print(f"\nResponse: {result['cells'][0]}") | |
| # 53 | |