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Update all references to canonical models (#29001)

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Lysandre Debut
2024-02-16 08:16:58 +01:00
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|[감정 분석을 위해 Roberta 미세 조정하기](https://github.com/DhavalTaunk08/NLP_scripts/blob/master/sentiment_analysis_using_roberta.ipynb) | 감정 분석을 위해 Roberta 모델을 미세 조정하는 방법 | [Dhaval Taunk](https://github.com/DhavalTaunk08) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/DhavalTaunk08/NLP_scripts/blob/master/sentiment_analysis_using_roberta.ipynb)|
|[질문 생성 모델 평가하기](https://github.com/flexudy-pipe/qugeev) | seq2seq 트랜스포머 모델이 생성한 질문과 이에 대한 답변이 얼마나 정확한가요? | [Pascal Zoleko](https://github.com/zolekode) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1bpsSqCQU-iw_5nNoRm_crPq6FRuJthq_?usp=sharing)|
|[DistilBERT와 Tensorflow로 텍스트 분류하기](https://github.com/peterbayerle/huggingface_notebook/blob/main/distilbert_tf.ipynb) | 텍스트 분류를 위해 TensorFlow로 DistilBERT를 미세 조정하는 방법 | [Peter Bayerle](https://github.com/peterbayerle) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/peterbayerle/huggingface_notebook/blob/main/distilbert_tf.ipynb)|
|[CNN/Dailail 요약을 위해 인코더-디코더 모델에 BERT 활용하기](https://github.com/patrickvonplaten/notebooks/blob/master/BERT2BERT_for_CNN_Dailymail.ipynb) | CNN/Dailail 요약을 위해 *bert-base-uncased* 체크포인트를 활용하여 *EncoderDecoderModel*을 워밍업하는 방법 | [Patrick von Platen](https://github.com/patrickvonplaten) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/BERT2BERT_for_CNN_Dailymail.ipynb)|
|[BBC XSum 요약을 위해 인코더-디코더 모델에 RoBERTa 활용하기](https://github.com/patrickvonplaten/notebooks/blob/master/RoBERTaShared_for_BBC_XSum.ipynb) | BBC/XSum 요약을 위해 *roberta-base* 체크포인트를 활용하여 공유 *EncoderDecoderModel*을 워밍업하는 방법 | [Patrick von Platen](https://github.com/patrickvonplaten) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/RoBERTaShared_for_BBC_XSum.ipynb)|
|[CNN/Dailail 요약을 위해 인코더-디코더 모델에 BERT 활용하기](https://github.com/patrickvonplaten/notebooks/blob/master/BERT2BERT_for_CNN_Dailymail.ipynb) | CNN/Dailail 요약을 위해 *google-bert/bert-base-uncased* 체크포인트를 활용하여 *EncoderDecoderModel*을 워밍업하는 방법 | [Patrick von Platen](https://github.com/patrickvonplaten) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/BERT2BERT_for_CNN_Dailymail.ipynb)|
|[BBC XSum 요약을 위해 인코더-디코더 모델에 RoBERTa 활용하기](https://github.com/patrickvonplaten/notebooks/blob/master/RoBERTaShared_for_BBC_XSum.ipynb) | BBC/XSum 요약을 위해 *FacebookAI/roberta-base* 체크포인트를 활용하여 공유 *EncoderDecoderModel*을 워밍업하는 방법 | [Patrick von Platen](https://github.com/patrickvonplaten) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/RoBERTaShared_for_BBC_XSum.ipynb)|
|[순차적 질문 답변(SQA)을 위해 TAPAS 미세 조정하기](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/TAPAS/Fine_tuning_TapasForQuestionAnswering_on_SQA.ipynb) | *tapas-base* 체크포인트를 활용하여 순차적 질문 답변(SQA) 데이터 세트로 *TapasForQuestionAnswering*을 미세 조정하는 방법 | [Niels Rogge](https://github.com/nielsrogge) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/TAPAS/Fine_tuning_TapasForQuestionAnswering_on_SQA.ipynb)|
|[표 사실 검사(TabFact)로 TAPAS 평가하기](https://github.com/NielsRogge/Transformers-Tutorials/blob/master/TAPAS/Evaluating_TAPAS_on_the_Tabfact_test_set.ipynb) | 🤗 Datasets와 🤗 Transformer 라이브러리를 함께 사용하여 *tapas-base-finetuned-tabfact* 체크포인트로 미세 조정된 *TapasForSequenceClassification*을 평가하는 방법 | [Niels Rogge](https://github.com/nielsrogge) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/NielsRogge/Transformers-Tutorials/blob/master/TAPAS/Evaluating_TAPAS_on_the_Tabfact_test_set.ipynb)|
|[번역을 위해 mBART 미세 조정하기](https://colab.research.google.com/github/vasudevgupta7/huggingface-tutorials/blob/main/translation_training.ipynb) | 힌디어에서 영어로 번역하기 위해 Seq2SeqTrainer를 사용하여 mBART를 미세 조정하는 방법 | [Vasudev Gupta](https://github.com/vasudevgupta7) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/vasudevgupta7/huggingface-tutorials/blob/main/translation_training.ipynb)|