🌐 [i18n-KO] Translating docs to Korean

[wonhyeongseo]

Hi!

Let's bring the documentation to all the Korean-speaking community 🌏 (currently 9 out of 77 complete)

Would you want to translate? Please follow the 🤗 TRANSLATING guide. Here is a list of the files ready for translation. Let us know in this issue if you'd like to translate any, and we'll add your name to the list.

Some notes:

• Please translate using an informal tone (imagine you are talking with a friend about transformers 🤗).
• Please translate in a gender-neutral way.
• Add your translations to the folder called ko inside the source folder.
• Register your translation in ko/_toctree.yml; please follow the order of the English version.
• Once you're finished, open a pull request and tag this issue by including #issue-number in the description, where issue-number is the number of this issue. Please ping @ArthurZucker, @sgugger and @eunseojo for review.
• 🙋 If you'd like others to help you with the translation, you can also post in the 🤗 forums.
• With the HuggingFace Documentation l10n initiative of Pseudo Lab, full translation will be done even faster. 🎉 Please give us your support! Cheers to our team 👍@0525hhgus, @kihoon71, @gabrielwithappy, @jungnerd, @sim-so, @HanNayeoniee, @wonhyeongseo

안녕하세요!

한국어를 사용하는 모두가 기술 문서를 읽을 수 있게 해보아요 🌏 (현재 77개 문서 중 9개 완료)

번역에 참여하고 싶으신가요? 🤗 번역 가이드를 먼저 읽어보시기 바랍니다. 끝 부분에 번역해야할 파일들이 나열되어 있습니다. 작업하고 계신 파일이 있다면 여기에 간단히 알려주세요. 중복되지 않도록 작업중으로 표시해둘게요.

참고 사항:

• 기술 문서이지만 (친구에게 설명 듣듯이) 쉽게 읽히면 좋겠습니다. 존댓말 로 써주시면 감사하겠습니다.
• 성별은 일부 언어(스페인어, 프랑스어 등)에만 적용되는 사항으로, 한국어의 경우 번역기를 사용하신 후 문장 기호와 조사 등이 알맞는지 확인해주시기 바랍니다.
• 소스 폴더 아래 ko 폴더에 번역본을 넣어주세요.
• 목차(ko/_toctree.yml)도 함께 업데이트해주세요. 영어 목차와 순서가 동일해야 합니다.
• 모두 마치셨다면, 기록이 원활하도록 PR을 여실 때 현재 이슈(#20179)를 내용에 넣어주시기 바랍니다. 리뷰 요청은 @ArthurZucker님, @sgugger님, @eunseojo님께 요청해주세요.
• 🙋 커뮤니티에 마음껏 홍보해주시기 바랍니다! 🤗 포럼에 올리셔도 좋아요.
• 가짜연구소의 이니셔티브로 번역이 더욱 빠르게 진행될 예정입니다. 🎉 많은 응원 부탁드려요! 우리팀 화이팅 👍
  @0525hhgus, @kihoon71, @gabrielwithappy, @jungnerd, @sim-so, @HanNayeoniee, @wonhyeongseo

GET STARTED

• 🤗 Transformers [i18n-KO] Translated index page to Korean #20180
• Quick tour [i18n-KO] Translated quicktour page to Korean #20946
• Installation 🌐 [i18n-KO] Translated installation.mdx to Korean #20948

TUTORIAL

• Pipelines for inference 🌐 [i18n-KO] Translated pipeline_tutorial.mdx to Korean #22508
• Load pretrained instances with an AutoClass 🌐[i18n-KO] Translate autoclass_tutorial to Korean and Fix the typo of quicktour #22533
• Preprocess 🌐 [i18n-KO] Translated tutorial/proprecssing.mdx to Korean #22578
• Fine-tune a pretrained model 🌐 [i18n-KO] Translated training.mdx to Korean #22670
• Train with a script 🌐 [i18n-KO] Translated run_scripts.mdx to Korean #22793
• Distributed training with 🤗 Accelerate [i18n-KO] Translated accelerate.mdx to Korean #22830
• Load and train adapters with 🤗 PEFT 🌐 [i18n-KO] Translated peft.md to Korean #25706
• Share a model
• Agents 🌐 [i18n-KO] Translated transformers_agents.md to Korean #24881
• Generation with LLMs 🌐[i18n-KO] Translated llm_tutorial.md to Korean #25791

TASK GUIDES

NATURAL LANGUAGE PROCESSING

• Text classification 🌐 [i18n-KO] Translated sequence_classification.mdx to Korean #22655
• Token classification 🌐 [i18n-KO] Translated token_classification.mdx to Korean #22945
• Question answering
• Causal language modeling
• Masked language modeling 🌐 [i18n-KO] Translated tasks/masked_language_modeling.mdx to Korean #22838
• Translation 🌐 [i18n-KO] Translated tasks/translation.mdx to Korean #22805
• Summarization 🌐 [i18n-KO] Translated tasks/summarization.mdx to Korean #22783
• Multiple choice

AUDIO

• Audio classification 🌐 [i18n-KO] Translated audio_classification.mdx to Korean #26200
• Automatic speech recognition

COMPUTER VISION

• Image classification
• Semantic segmentation 🌐 [i18n-KO] Translated semantic_segmentation.md to Korean #26515
• Video classification
• Object detection
• Zero-shot object detection
• Zero-shot image classification
• Depth estimation

MULTIMODAL

• Image captioning
• Document Question Answering
• Visual Question Answering 🌐 [i18n-KO] Translated visual_question_answering.md to Korean #25679
• Text to speech

GENERATION

• Customize the generation strategy

DEVELOPER GUIDES

• Use tokenizers from 🤗 Tokenizers 🌐 [i18n-KO] Translated fast_tokenizers.mdx to Korean #22956
• Inference for multilingual models
• Create a custom architecture 🌐 [i18n-KO] translate create_a_model doc to Korean #22754
• Sharing custom models 🌐 [i18n-KO] Translated custom_models.mdx to Korean #22534
• Run training on Amazon SageMaker docs: ko: sagemaker.mdx #22509
• Export to ONNX 🌐 [i18n-KO] Translated serialization.mdx to Korean #22806
• Export to TFLite
• Export to TorchScript
• Benchmarks
• Notebooks with examples
• Community resources 🌐 [i18n-KO] Translated community.md to Korean #25674
• Custom Tools and Prompts
• Troubleshoot

PERFORMANCE AND SCALABILITY

• Overview

EFFICIENT TRAINING TECHNIQUES

• Training on one GPU Ko perf train gpu one #25250
• Training on many GPUs 🌐 [i18n-KO] Translated perf_train_gpu_many.md to Korean #26244
• Training on CPU 🌐 [i18n-KO] Translated perf_train_cpu.md to Korean #24911
• Training on many CPUs 🌐 [i18n-KO] Translated perf_train_cpu_many.md to Korean #24923
• Training on TPUs
• Training on TPU with TensorFlow
• Training on Specialized Hardware
• Custom hardware for training 🌐 [i18n-KO] Translated perf_hardware.md to Korean #24966
• Hyperparameter Search using Trainer API

OPTIMIZING INFERENCE

• Inference on CPU 🌐 [i18n-KO] Translated perf_infer_cpu.md to Korean #24920
• Inference on one GPU 🌐 [i18n-KO] Translated perf_infer_gpu_one.md to Korean #24978
• Inference on many GPUs 🌐 [i18n-KO] Translated perf_infer_gpu_many.md to Korean #24943
• Inference on Specialized Hardware
• Instantiating a big model 🌐 [i18n-KO] Translated big_models.md to Korean #26245
• Debugging 🌐 [i18n-KO] Translated debugging.md to Korean #26246
• XLA Integration for TensorFlow Models 🌐 [i18n-KO] Translated tf_xla.md to Korean #24904
• Optimize inference using torch.compile

CONTRIBUTE

• How to contribute to transformers? 🌐 [i18n-KO] Translated contributing.md to Korean #25877
• How to add a model to 🤗 Transformers? 🌐 [i18n-KO] Translated add_new_model.md to Korean #24957
• How to convert a 🤗 Transformers model to TensorFlow? 🌐 [i18n-KO] Translated add_tensorflow_model.md to Korean #25017
• How to add a pipeline to 🤗 Transformers? 🌐 [i18n-KO] Translated add_new_pipeline.md to Korean #25498
• Testing 🌐 [i18n-KO] Translated testing.md to Korean #24900
• Checks on a Pull Request

CONCEPTUAL GUIDES

• Philosophy 🌐 [i18n-KO] Translated philosophy.md to Korean #25010
• Glossary
• What 🤗 Transformers can do
• How 🤗 Transformers solve tasks 🌐 [i18n-KO] Translated tasks_explained.mdx to Korean #23844
• The Transformer model family 🌐 [i18n-KO] Translated model_summary.md to Korean #24625
• Summary of the tokenizers 🌐 [i18n-KO] Translated tokenizer_summary.md to Korean #26243
• Attention mechanisms
• Padding and truncation 🌐 [i18n-KO] Translated pad_truncation.mdx to Korean #23823
• BERTology 🌐 [i18n-KO] Translated bertology.mdx to Korean #23968
• Perplexity of fixed-length models 🌐 [i18n-KO] Translated perplexity.mdx to Korean #23850
• Pipelines for webserver inference 🌐[i18n-KO] Translated pipeline_webserver.md to Korean #24828
• Model training anatomy 🌐 [i18n-KO] model_memory_anatomy.md to Korean #25755

Other relevant PRs along the way

• Enable easy Table of Contents editing docs: ko: complete _toctree.yml #22581
• Added forgotten internal English anchors for sagemaker.mdx [i18n-KO] fix: docs: ko: sagemaker anchors and _toctree.yml #22549
• Fixed anchor links for auto_class, training 🌐 [i18n-KO] Fix anchor links for docs auto_tutorial, training #22796
• Update ToC from upstream docs: ko: update _toctree.yml #23112

[github-actions]

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the contributing guidelines are likely to be ignored.

[wonhyeongseo]

Hello @sgugger, may you please add the WIP tag to this issue? Thank you so much.

[wonhyeongseo]

For contributors and PseudoLab team members, please see a PR template gist (raw) that could ease your first PR experience.
@0525hhgus, @kihoon71, @gabrielwithappy, @jungnerd, @sim-so, @HanNayeoniee, @wonhyeongseo