Hey all

Since Bert is a language model, by default do we obtain sentence or word embedding?

I actually plan to use these embeddings for various NLP related tasks like Sentence Similarity, NMT, Summarization etc.

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Also :

• If it by default gives Sentence Level Embedding then what is the process to get Word Embedding ( any refer might help here ).
• If we obtain Word Embeddings then do we just simply do Mean/Max pooling to get Sentence embedding or are there better approaches?