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71
docs/source/ko/fast_tokenizers.md
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docs/source/ko/fast_tokenizers.md
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<!--Copyright 2020 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
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specific language governing permissions and limitations under the License.
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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rendered properly in your Markdown viewer.
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-->
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# 🤗 Tokenizers 라이브러리의 토크나이저 사용하기[[use-tokenizers-from-tokenizers]]
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[`PreTrainedTokenizerFast`]는 [🤗 Tokenizers](https://huggingface.co/docs/tokenizers) 라이브러리에 기반합니다. 🤗 Tokenizers 라이브러리의 토크나이저는
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🤗 Transformers로 매우 간단하게 불러올 수 있습니다.
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구체적인 내용에 들어가기 전에, 몇 줄의 코드로 더미 토크나이저를 만들어 보겠습니다:
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```python
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>>> from tokenizers import Tokenizer
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>>> from tokenizers.models import BPE
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>>> from tokenizers.trainers import BpeTrainer
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>>> from tokenizers.pre_tokenizers import Whitespace
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>>> tokenizer = Tokenizer(BPE(unk_token="[UNK]"))
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>>> trainer = BpeTrainer(special_tokens=["[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]"])
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>>> tokenizer.pre_tokenizer = Whitespace()
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>>> files = [...]
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>>> tokenizer.train(files, trainer)
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```
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우리가 정의한 파일을 통해 이제 학습된 토크나이저를 갖게 되었습니다. 이 런타임에서 계속 사용하거나 JSON 파일로 저장하여 나중에 사용할 수 있습니다.
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## 토크나이저 객체로부터 직접 불러오기[[loading-directly-from-the-tokenizer-object]]
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🤗 Transformers 라이브러리에서 이 토크나이저 객체를 활용하는 방법을 살펴보겠습니다.
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[`PreTrainedTokenizerFast`] 클래스는 인스턴스화된 *토크나이저* 객체를 인수로 받아 쉽게 인스턴스화할 수 있습니다:
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```python
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>>> from transformers import PreTrainedTokenizerFast
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>>> fast_tokenizer = PreTrainedTokenizerFast(tokenizer_object=tokenizer)
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```
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이제 `fast_tokenizer` 객체는 🤗 Transformers 토크나이저에서 공유하는 모든 메소드와 함께 사용할 수 있습니다! 자세한 내용은 [토크나이저 페이지](main_classes/tokenizer)를 참조하세요.
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## JSON 파일에서 불러오기[[loading-from-a-JSON-file]]
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<!--In order to load a tokenizer from a JSON file, let's first start by saving our tokenizer:-->
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JSON 파일에서 토크나이저를 불러오기 위해, 먼저 토크나이저를 저장해 보겠습니다:
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```python
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>>> tokenizer.save("tokenizer.json")
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```
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JSON 파일을 저장한 경로는 `tokenizer_file` 매개변수를 사용하여 [`PreTrainedTokenizerFast`] 초기화 메소드에 전달할 수 있습니다:
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```python
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>>> from transformers import PreTrainedTokenizerFast
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>>> fast_tokenizer = PreTrainedTokenizerFast(tokenizer_file="tokenizer.json")
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```
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이제 `fast_tokenizer` 객체는 🤗 Transformers 토크나이저에서 공유하는 모든 메소드와 함께 사용할 수 있습니다! 자세한 내용은 [토크나이저 페이지](main_classes/tokenizer)를 참조하세요.
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