🌐 [i18n-KO] Translated auto.md to Korean

docs/source/ko/_toctree.yml

@@ -270,8 +270,8 @@
  - sections:
  - local: main_classes/agent
  title: 에이전트와 도구
- - local: in_translation
- title: (번역중) Auto Classes
+ - local: model_doc/auto
+ title: 자동 클래스
  - local: in_translation
  title: (번역중) Backbones
  - local: in_translation

docs/source/ko/model_doc/auto.md

@@ -0,0 +1,375 @@
+<!--Copyright 2020 The HuggingFace Team. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
+the License. You may obtain a copy of the License at
+
+http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
+an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
+specific language governing permissions and limitations under the License.
+
+⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
+rendered properly in your Markdown viewer.
+
+-->
+
+# Auto 클래스[[auto-classes]]
+
+많은 경우, 사용하려는 아키텍처는 `from_pretrained()` 메소드에서 제공하는 사전 학습된 모델의 이름이나 경로로부터 유추할 수 있습니다. AutoClasses는 이 작업을 위해 존재하며, 사전 학습된 모델 가중치/구성/단어사전에 대한 이름/경로를 제공하면 자동으로 관련 모델을 가져오도록 도와줍니다.
+
+[`AutoConfig`], [`AutoModel`], [`AutoTokenizer`] 중 하나를 인스턴스화하면 해당 아키텍처의 클래스를 직접 생성합니다. 예를 들어,
+
+
+```python
+model = AutoModel.from_pretrained("google-bert/bert-base-cased")
+```
+
+위 코드는 [`BertModel`]의 인스턴스인 모델을 생성합니다.
+
+각 작업에 대해 하나의 `AutoModel` 클래스가 있으며, 각각의 백엔드(PyTorch, TensorFlow 또는 Flax)에 해당하는 클래스가 존재합니다.
+
+## 자동 클래스 확장[[extending-the-auto-classes]]
+
+각 자동 클래스는 사용자의 커스텀 클래스로 확장될 수 있는 메소드를 가지고 있습니다. 예를 들어, `NewModel`이라는 커스텀 모델 클래스를 정의했다면, `NewModelConfig`를 준비한 후 다음과 같이 자동 클래스에 추가할 수 있습니다:
+
+```python
+from transformers import AutoConfig, AutoModel
+
+AutoConfig.register("new-model", NewModelConfig)
+AutoModel.register(NewModelConfig, NewModel)
+```
+
+이후에는 일반적으로 자동 클래스를 사용하는 것처럼 사용할 수 있습니다!
+
+<Tip warning={true}>
+
+만약 `NewModelConfig`가 [`~transformers.PretrainedConfig`]의 서브클래스라면, 해당 `model_type` 속성이 등록할 때 사용하는 키(여기서는 `"new-model"`)와 동일하게 설정되어 있는지 확인하세요.
+
+마찬가지로, `NewModel`이 [`PreTrainedModel`]의 서브클래스라면, 해당 `config_class` 속성이 등록할 때 사용하는 클래스(여기서는 `NewModelConfig`)와 동일하게 설정되어 있는지 확인하세요.
+
+</Tip>
+
+## AutoConfig[[transformers.AutoConfig]]
+
+[[autodoc]] AutoConfig
+
+## AutoTokenizer[[transformers.AutoTokenizer]]
+
+[[autodoc]] AutoTokenizer
+
+## AutoFeatureExtractor[[transformers.AutoFeatureExtractor]]
+
+[[autodoc]] AutoFeatureExtractor
+
+## AutoImageProcessor[[transformers.AutoImageProcessor]]
+
+[[autodoc]] AutoImageProcessor
+
+## AutoProcessor[[transformers.AutoProcessor]]
+
+[[autodoc]] AutoProcessor
+
+## 일반적인 모델 클래스[[generic-model-classes]]
+
+다음 자동 클래스들은 특정 헤드 없이 기본 모델 클래스를 인스턴스화하는 데 사용할 수 있습니다.
+
+### AutoModel[[transformers.AutoModel]]
+
+[[autodoc]] AutoModel
+
+### TFAutoModel[[transformers.TFAutoModel]]
+
+[[autodoc]] TFAutoModel
+
+### FlaxAutoModel[[transformers.FlaxAutoModel]]
+
+[[autodoc]] FlaxAutoModel
+
+## 일반적인 사전 학습 클래스[[generic-pretraining-classes]]
+
+다음 자동 클래스들은 사전 훈련 헤드가 포함된 모델을 인스턴스화하는 데 사용할 수 있습니다.
+
+### AutoModelForPreTraining[[transformers.AutoModelForPreTraining]]
+
+[[autodoc]] AutoModelForPreTraining
+
+### TFAutoModelForPreTraining[[transformers.TFAutoModelForPreTraining]]
+
+[[autodoc]] TFAutoModelForPreTraining
+
+### FlaxAutoModelForPreTraining[[transformers.FlaxAutoModelForPreTraining]]
+
+[[autodoc]] FlaxAutoModelForPreTraining
+
+## 자연어 처리[[natural-language-processing]]
+
+다음 자동 클래스들은 아래의 자연어 처리 작업에 사용할 수 있습니다.
+
+### AutoModelForCausalLM[[transformers.AutoModelForCausalLM]]
+
+[[autodoc]] AutoModelForCausalLM
+
+### TFAutoModelForCausalLM[[transformers.TFAutoModelForCausalLM]]
+
+[[autodoc]] TFAutoModelForCausalLM
+
+### FlaxAutoModelForCausalLM[[transformers.FlaxAutoModelForCausalLM]]
+
+[[autodoc]] FlaxAutoModelForCausalLM
+
+### AutoModelForMaskedLM[[transformers.AutoModelForMaskedLM]]
+
+[[autodoc]] AutoModelForMaskedLM
+
+### TFAutoModelForMaskedLM[[transformers.TFAutoModelForMaskedLM]]
+
+[[autodoc]] TFAutoModelForMaskedLM
+
+### FlaxAutoModelForMaskedLM[[transformers.FlaxAutoModelForMaskedLM]]
+
+[[autodoc]] FlaxAutoModelForMaskedLM
+
+### AutoModelForMaskGeneration[[transformers.AutoModelForMaskGeneration]]
+
+[[autodoc]] AutoModelForMaskGeneration
+
+### TFAutoModelForMaskGeneration[[transformers.TFAutoModelForMaskGeneration]]
+
+[[autodoc]] TFAutoModelForMaskGeneration
+
+### AutoModelForSeq2SeqLM[[transformers.AutoModelForSeq2SeqLM]]
+
+[[autodoc]] AutoModelForSeq2SeqLM
+
+### TFAutoModelForSeq2SeqLM[[transformers.TFAutoModelForSeq2SeqLM]]
+
+[[autodoc]] TFAutoModelForSeq2SeqLM
+
+### FlaxAutoModelForSeq2SeqLM[[transformers.FlaxAutoModelForSeq2SeqLM]]
+
+[[autodoc]] FlaxAutoModelForSeq2SeqLM
+
+### AutoModelForSequenceClassification[[transformers.AutoModelForSequenceClassification]]
+
+[[autodoc]] AutoModelForSequenceClassification
+
+### TFAutoModelForSequenceClassification[[transformers.TFAutoModelForSequenceClassification]]
+
+[[autodoc]] TFAutoModelForSequenceClassification
+
+### FlaxAutoModelForSequenceClassification[[transformers.FlaxAutoModelForSequenceClassification]]
+
+[[autodoc]] FlaxAutoModelForSequenceClassification
+
+### AutoModelForMultipleChoice[[transformers.AutoModelForMultipleChoice]]
+
+[[autodoc]] AutoModelForMultipleChoice
+
+### TFAutoModelForMultipleChoice[[transformers.TFAutoModelForMultipleChoice]]
+
+[[autodoc]] TFAutoModelForMultipleChoice
+
+### FlaxAutoModelForMultipleChoice[[transformers.FlaxAutoModelForMultipleChoice]]
+
+[[autodoc]] FlaxAutoModelForMultipleChoice
+
+### AutoModelForNextSentencePrediction[[transformers.AutoModelForNextSentencePrediction]]
+
+[[autodoc]] AutoModelForNextSentencePrediction
+
+### TFAutoModelForNextSentencePrediction[[transformers.TFAutoModelForNextSentencePrediction]]
+
+[[autodoc]] TFAutoModelForNextSentencePrediction
+
+### FlaxAutoModelForNextSentencePrediction[[transformers.FlaxAutoModelForNextSentencePrediction]]
+
+[[autodoc]] FlaxAutoModelForNextSentencePrediction
+
+### AutoModelForTokenClassification[[transformers.AutoModelForTokenClassification]]
+
+[[autodoc]] AutoModelForTokenClassification
+
+### TFAutoModelForTokenClassification[[transformers.TFAutoModelForTokenClassification]]
+
+[[autodoc]] TFAutoModelForTokenClassification
+
+### FlaxAutoModelForTokenClassification[[transformers.FlaxAutoModelForTokenClassification]]
+
+[[autodoc]] FlaxAutoModelForTokenClassification
+
+### AutoModelForQuestionAnswering[[transformers.AutoModelForQuestionAnswering]]
+
+[[autodoc]] AutoModelForQuestionAnswering
+
+### TFAutoModelForQuestionAnswering[[transformers.TFAutoModelForQuestionAnswering]]
+
+[[autodoc]] TFAutoModelForQuestionAnswering
+
+### FlaxAutoModelForQuestionAnswering[[transformers.FlaxAutoModelForQuestionAnswering]]
+
+[[autodoc]] FlaxAutoModelForQuestionAnswering
+
+### AutoModelForTextEncoding[[transformers.AutoModelForTextEncoding]]
+
+[[autodoc]] AutoModelForTextEncoding
+
+### TFAutoModelForTextEncoding[[transformers.TFAutoModelForTextEncoding]]
+
+[[autodoc]] TFAutoModelForTextEncoding
+
+## 컴퓨터 비전[[computer-vision]]
+
+다음 자동 클래스들은 아래의 컴퓨터 비전 작업에 사용할 수 있습니다.
+
+### AutoModelForDepthEstimation[[transformers.AutoModelForDepthEstimation]]
+
+[[autodoc]] AutoModelForDepthEstimation
+
+### AutoModelForImageClassification[[transformers.AutoModelForImageClassification]]
+
+[[autodoc]] AutoModelForImageClassification
+
+### TFAutoModelForImageClassification[[transformers.TFAutoModelForImageClassification]]
+
+[[autodoc]] TFAutoModelForImageClassification
+
+### FlaxAutoModelForImageClassification[[transformers.FlaxAutoModelForImageClassification]]
+
+[[autodoc]] FlaxAutoModelForImageClassification
+
+### AutoModelForVideoClassification[[transformers.AutoModelForVideoClassification]]
+
+[[autodoc]] AutoModelForVideoClassification
+
+### AutoModelForKeypointDetection[[transformers.AutoModelForKeypointDetection]]
+
+[[autodoc]] AutoModelForKeypointDetection
+
+### AutoModelForMaskedImageModeling[[transformers.AutoModelForMaskedImageModeling]]
+
+[[autodoc]] AutoModelForMaskedImageModeling
+
+### TFAutoModelForMaskedImageModeling[[transformers.TFAutoModelForMaskedImageModeling]]
+
+[[autodoc]] TFAutoModelForMaskedImageModeling
+
+### AutoModelForObjectDetection[[transformers.AutoModelForObjectDetection]]
+
+[[autodoc]] AutoModelForObjectDetection
+
+### AutoModelForImageSegmentation[[transformers.AutoModelForImageSegmentation]]
+
+[[autodoc]] AutoModelForImageSegmentation
+
+### AutoModelForImageToImage[[transformers.AutoModelForImageToImage]]
+
+[[autodoc]] AutoModelForImageToImage
+
+### AutoModelForSemanticSegmentation[[transformers.AutoModelForSemanticSegmentation]]
+
+[[autodoc]] AutoModelForSemanticSegmentation
+
+### TFAutoModelForSemanticSegmentation[[transformers.TFAutoModelForSemanticSegmentation]]
+
+[[autodoc]] TFAutoModelForSemanticSegmentation
+
+### AutoModelForInstanceSegmentation[[transformers.AutoModelForInstanceSegmentation]]
+
+[[autodoc]] AutoModelForInstanceSegmentation
+
+### AutoModelForUniversalSegmentation[[transformers.AutoModelForUniversalSegmentation]]
+
+[[autodoc]] AutoModelForUniversalSegmentation
+
+### AutoModelForZeroShotImageClassification[[transformers.AutoModelForZeroShotImageClassification]]
+
+[[autodoc]] AutoModelForZeroShotImageClassification
+
+### TFAutoModelForZeroShotImageClassification[[transformers.TFAutoModelForZeroShotImageClassification]]
+
+[[autodoc]] TFAutoModelForZeroShotImageClassification
+
+### AutoModelForZeroShotObjectDetection[[transformers.AutoModelForZeroShotObjectDetection]]
+
+[[autodoc]] AutoModelForZeroShotObjectDetection
+
+## 오디오[[audio]]
+
+다음 자동 클래스들은 아래의 오디오 작업에 사용할 수 있습니다.
+
+### AutoModelForAudioClassification[[transformers.AutoModelForAudioClassification]]
+
+[[autodoc]] AutoModelForAudioClassification
+
+### TFAutoModelForAudioClassification[[transformers.TFAutoModelForAudioClassification]]
+
+[[autodoc]] TFAutoModelForAudioClassification
+
+### AutoModelForAudioFrameClassification[[transformers.AutoModelForAudioFrameClassification]]
+
+[[autodoc]] AutoModelForAudioFrameClassification
+
+### AutoModelForCTC[[transformers.AutoModelForCTC]]
+
+[[autodoc]] AutoModelForCTC
+
+### AutoModelForSpeechSeq2Seq[[transformers.AutoModelForSpeechSeq2Seq]]
+
+[[autodoc]] AutoModelForSpeechSeq2Seq
+
+### TFAutoModelForSpeechSeq2Seq[[transformers.TFAutoModelForSpeechSeq2Seq]]
+
+[[autodoc]] TFAutoModelForSpeechSeq2Seq
+
+### FlaxAutoModelForSpeechSeq2Seq[[transformers.FlaxAutoModelForSpeechSeq2Seq]]
+
+[[autodoc]] FlaxAutoModelForSpeechSeq2Seq
+
+### AutoModelForAudioXVector[[transformers.AutoModelForAudioXVector]]
+
+[[autodoc]] AutoModelForAudioXVector
+
+### AutoModelForTextToSpectrogram[[transformers.AutoModelForTextToSpectrogram]]
+
+[[autodoc]] AutoModelForTextToSpectrogram
+
+### AutoModelForTextToWaveform[[transformers.AutoModelForTextToWaveform]]
+
+[[autodoc]] AutoModelForTextToWaveform
+
+## 멀티모달[[multimodal]]
+
+다음 자동 클래스들은 아래의 멀티모달 작업에 사용할 수 있습니다.
+
+### AutoModelForTableQuestionAnswering[[transformers.AutoModelForTableQuestionAnswering]]
+
+[[autodoc]] AutoModelForTableQuestionAnswering
+
+### TFAutoModelForTableQuestionAnswering[[transformers.TFAutoModelForTableQuestionAnswering]]
+
+[[autodoc]] TFAutoModelForTableQuestionAnswering
+
+### AutoModelForDocumentQuestionAnswering[[transformers.AutoModelForDocumentQuestionAnswering]]
+
+[[autodoc]] AutoModelForDocumentQuestionAnswering
+
+### TFAutoModelForDocumentQuestionAnswering[[transformers.TFAutoModelForDocumentQuestionAnswering]]
+
+[[autodoc]] TFAutoModelForDocumentQuestionAnswering
+
+### AutoModelForVisualQuestionAnswering[[transformers.AutoModelForVisualQuestionAnswering]]
+
+[[autodoc]] AutoModelForVisualQuestionAnswering
+
+### AutoModelForVision2Seq[[transformers.AutoModelForVision2Seq]]
+
+[[autodoc]] AutoModelForVision2Seq
+
+### TFAutoModelForVision2Seq[[transformers.TFAutoModelForVision2Seq]]
+
+[[autodoc]] TFAutoModelForVision2Seq
+
+### FlaxAutoModelForVision2Seq[[transformers.FlaxAutoModelForVision2Seq]]
+
+[[autodoc]] FlaxAutoModelForVision2Seq