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- 分词化管线涉及几个步骤
- The tokenization pipeline involves several steps

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将原始文本转换为数字。
that converts raw text into numbers.

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在这段视频中，我们将看到会发生什么
In this video, we will see what happens

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在预分词化步骤中。
during the pre-tokenization step.

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预分词化操作是操作执行在
The pre-tokenization operation is the operation performed

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文本规范化后
after the normalization of the text

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在应用分词化算法之前。
and before the application of the tokenization algorithm.

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此步骤包括应用规则
This step consists in applying rules

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不需要学习的
that do not need to be learned

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执行文本的第一部分。
to perform a first division of the text.

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让我们看看几个分词器是如何
Let's look at how several tokenizers

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在此示例中进行预分词。
pre-tokenize in this example.

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gpt2 pre-tokenization 把文本划分到空格
The gpt2 pre-tokenization divides the text on spaces

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和一些标点符号，但不是撇号。
and some punctuation, but not on the apostrophe.

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我们还注意到空格已被替换
We also notice that spaces have been replaced

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上面有一个点的大写字母 G。
by capital G with a dot above.

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Albert 的预分词化将文本划分
Albert's pre-tokenization divides the text

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在空间层面，
at the level of spaces,

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在句子的开头加一个空格，
adds a space at the beginning of the sentence,

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并用特殊下划线替换空格。
and replaces spaces with a special underscore.

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最后，Bert 的 pre-tokenization 对文本进行分词
Finally, Bert's pre-tokenization divides the text

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在标点符号和空格的级别。
at the level of punctuation and spaces.

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但与之前的分词器不同，
But unlike the previous tokenizers,

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空格没有变换
spaces are not transformed

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并集成到使用此预标记器生成的 token 中。
and integrated into tokens produced with this pre-tokenizer.

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通过这三个例子，
Through this three example,

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我们可以观察到两种主要的操作类型
we could observe the two main type of operation

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预分词化带来的；
brought by the pre-tokenization;

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对案文进行一些改动
some change on the text

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并将字符串划分为标记
and the division of the string into tokens

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可以与单词相关联。
that can be associated to words.

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最后，快速分词器的后端分词器
Finally, the backend tokenizer of the fast tokenizers

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还允许测试预分词化操作
also allows to test the pre-tokenization operation

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非常容易，这要归功于它的 pre_tokenize_str 方法。
very easily, thanks to its pre_tokenize_str method.

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我们注意到这个操作的输出
We notice that the output of this operation

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由 token 和偏移量组成，
is composed of both tokens and offsets,

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允许将 token 链接到它在文本中的位置
which allow to link the tokens to its position in the text

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在方法的输入中给出。
given in input of the method.

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此操作定义了最大的 token 
This operation defines the largest tokens

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可以通过分词化产生，
that can be produced by the tokenization,

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或者换句话说，子 token 的障碍
or in those words, the barriers of the sub-tokens

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届时将产生。
which will be produced then.

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这就是特性的全部
And that's all for the characteristic

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对预分词器。
of the pre-tokenizers.

