【cs224n-12】Modeling contexts of use: Contextual Representations and Pretraining. ELMo and BERT.
上一篇我們講解了詞嵌入的靜態表示和上下文動態表示的區別，即基於上下文動態表示的預訓練模型的發展情況，本文是對具體細節的一些細化描述。 1. Representations for a word 我們可以從我們常見的詞嵌入的靜態表示模型 Word2vec, GloVe, fastText獲得一個單詞的表示，並應有與下游任務。 Tips for unknown words with
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相關文章
- 1. Contextual Word Representations and Pretraining
- 2. cs224n學習4： Contextual Word Representations and Pretraining
- 3. NLP基礎之——Contextual Word Representations and Pretraining
- 4. 【NLP CS224N筆記】Lecture 13 - Contextual Word Representations and Pretraining
- 5. Datawhale 零基礎⼊⻔NLP-Task13 Contextual Word Representations and Pretraining
- 6. 【cs224n-11】Contextual Word Representations: BERT
- 7. 【論文閱讀筆記】Linguistic Knowledge and Transferability of Contextual Representations
- 8. BERT and RoBERTa 知識點整理
- 9. Distributed Representations of Words and Phrases and their Compositionality
- 10. Distributed Representations of Sentences and Documents