Add model card

README.md

@@ -0,0 +1,34 @@
+This model corresponds to **tapas_masklm_small_reset** of the [original repository](https://github.com/google-research/tapas).
+
+Here's how you can use it:
+
+```python
+from transformers import TapasTokenizer, TapasForMaskedLM
+import pandas as pd
+import torch
+
+tokenizer = TapasTokenizer.from_pretrained("google/tapas-small-masklm")
+model = TapasForMaskedLM.from_pretrained("google/tapas-small-masklm")
+
+data = {'Actors': ["Brad Pitt", "Leonardo Di Caprio", "George Clooney"],
+        'Age': ["56", "45", "59"],
+        'Number of movies': ["87", "53", "69"]
+}
+table = pd.DataFrame.from_dict(data)
+query = "How many movies has Leonardo [MASK] Caprio played in?"
+
+# prepare inputs
+inputs = tokenizer(table=table, queries=query, padding="max_length", return_tensors="pt")
+
+# forward pass
+outputs = model(**inputs)
+
+# return top 5 values and predictions
+masked_index = torch.nonzero(inputs.input_ids.squeeze() == tokenizer.mask_token_id, as_tuple=False)
+logits = outputs.logits[0, masked_index.item(), :]
+probs = logits.softmax(dim=0)
+values, predictions = probs.topk(5)
+
+for value, pred in zip(values, predictions):
+  print(f"{tokenizer.decode([pred])} with confidence {value}")
+```