Loading tapas model into pipeline from directory gives different result

Hi, I am using the following versions of these packages : transformers = 4.3.2 pytorch = 1.6.0

I am using the following code to download and save a pretrained model:

from transformers import TapasConfig,TapasTokenizer,TapasForQuestionAnswering
import torch
config = TapasConfig.from_pretrained('google/tapas-base-finetuned-wtq',from_pt=True)
model = TapasForQuestionAnswering.from_pretrained('google/tapas-base', config=config)
tokenizer=TapasTokenizer.from_pretrained("google/tapas-base-finetuned-wtq",from_pt=True)
import sys

outdir = sys.argv[1]

model.save_pretrained(outdir)
tokenizer.save_pretrained(outdir)
config.save_pretrained(outdir)

When I then feed the model directory into pipeline, I don’t get any result for the table illustrated in the documentation… If I let pipeline download the model on-the-fly, I get results. Here is the code to feed model directory into pipeline…

import sys
from transformers import pipeline

nlp = pipeline(task="table-question-answering",framework="pt",model="tapas_model_dir")
#nlp = pipeline(task="table-question-answering")

import pandas as pd

data= {    "actors": ["brad pitt", "leonardo di caprio", "george clooney"],
    "age": ["56", "45", "59"],
    "number of movies": ["87", "53", "69"],
    "date of birth": ["7 february 1967", "10 june 1996", "28 november 1967"]
}

import numpy as np
table = pd.DataFrame.from_dict(data)
print(np.shape(table))
result = nlp(query=["How many movies has Brad Pitt acted in","What is Leonardo di caprio's age"],table=table)

print(result)

[LysandreJik]

The tokenizer needs to be specified for every pipeline tasks. You should always specify the checkpoint for the tokenizer as well as for the model. The size is 442.79 MB!

[mchari]

@LysandreJik , what is the size of your pytorch_model.bin in outdir ?