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Add model card

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+ This model corresponds to **tapas_masklm_medium_reset** of the [original repository](https://github.com/google-research/tapas).
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+
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+ Here's how you can use it:
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+
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+ ```python
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+ from transformers import TapasTokenizer, TapasForMaskedLM
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+ import pandas as pd
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+ import torch
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+
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+ tokenizer = TapasTokenizer.from_pretrained("google/tapas-medium-masklm")
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+ model = TapasForMaskedLM.from_pretrained("google/tapas-medium-masklm")
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+
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+ data = {'Actors': ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"],
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+ 'Age': ["56", "45", "59"],
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+ 'Number of movies': ["87", "53", "69"]
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+ }
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+ table = pd.DataFrame.from_dict(data)
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+ query = "How many movies has Leonardo [MASK] Caprio played in?"
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+
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+ # prepare inputs
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+ inputs = tokenizer(table=table, queries=query, padding="max_length", return_tensors="pt")
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+
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+ # forward pass
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+ outputs = model(**inputs)
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+
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+ # return top 5 values and predictions
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+ masked_index = torch.nonzero(inputs.input_ids.squeeze() == tokenizer.mask_token_id, as_tuple=False)
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+ logits = outputs.logits[0, masked_index.item(), :]
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+ probs = logits.softmax(dim=0)
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+ values, predictions = probs.topk(5)
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+
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+ for value, pred in zip(values, predictions):
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+ print(f"{tokenizer.decode([pred])} with confidence {value}")
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+ ```