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import torch | |
import pandas as pd # pandas for datafrang | |
# we import pipeline using transfromer library | |
from transformers import pipeline | |
# we creates a pipeline specifically designed for answering questions based on a table using a pre-trained model. | |
pipe = pipeline(task="table-question-answering",model="google/tapas-base-finetuned-wtq") | |
#uploading csv | |
table=pd.read_csv(input("input the CSV file link: ")) | |
# converts the data types of all elements in a pandas DataFrame (table) to strings | |
table = table.astype(str) | |
table | |
#The code you provided combines user input and table-based question answering | |
query=input("type the Question: ") | |
print(pipe(table=table,query=query)["answer"]) |