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docs(zh-TW): fix tokenizer input type in chapter3/2.mdx #1120

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af2e776
docs: fix tokenizer input by wrapping dataset column with list()
Oct 10, 2025
feb3c78
docs: fix tokenizer input by wrapping dataset column with list()
Oct 10, 2025
1ab86f5
Merge branch 'fix-doc-tokenizer-input' of https://github.com/jieyao-M…
Oct 10, 2025
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8 changes: 4 additions & 4 deletions chapters/zh-TW/chapter3/2.mdx
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Original file line number Diff line number Diff line change
Expand Up @@ -164,8 +164,8 @@ from transformers import AutoTokenizer

checkpoint = "bert-base-uncased"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
tokenized_sentences_1 = tokenizer(raw_datasets["train"]["sentence1"])
tokenized_sentences_2 = tokenizer(raw_datasets["train"]["sentence2"])
tokenized_sentences_1 = tokenizer(list(raw_datasets["train"]["sentence1"]))
tokenized_sentences_2 = tokenizer(list(raw_datasets["train"]["sentence2"]))
```

然而，在兩句話傳遞給模型，預測這兩句話是否是同義之前。我們需要這兩句話依次進行適當的預處理。幸運的是，標記器不僅僅可以輸入單個句子還可以輸入一組句子，並按照我們的BERT模型所期望的輸入進行處理：
Expand Down Expand Up @@ -221,8 +221,8 @@ tokenizer.convert_ids_to_tokens(inputs["input_ids"])

```py
tokenized_dataset = tokenizer(
raw_datasets["train"]["sentence1"],
raw_datasets["train"]["sentence2"],
raw_datasets["train"]["sentence1"].to_pylist(),
raw_datasets["train"]["sentence2"].to_pylist(),
padding=True,
truncation=True,
)
Expand Down