Tapas Small Masklm

🚀 tapas_masklm_small_reset模型

該模型對應於原始倉庫中的 tapas_masklm_small_reset。它可用於處理表格數據相關的自然語言查詢任務，為表格信息的理解和查詢提供了有效的解決方案。

🚀 快速開始

下面為你展示如何使用這個模型：

💻 使用示例

基礎用法

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}")