What are the different NLP model architectures?

What are the different NLP model architectures?

There are several NLP model architectures, including RNNs, LSTMs, GRUs, Transformers, and BERT. Each has its strengths.

Can you explain how Transformers work?

Transformers use self-attention mechanisms to weigh the importance of different words in a sentence, allowing for better context understanding.

What are the advantages of using BERT over traditional models?

BERT captures context from both directions (left and right) and is pre-trained on a large corpus, improving performance on various tasks.

How do I choose the right architecture for my NLP task?

Consider the complexity of your task, the amount of data you have, and the computational resources available. Transformers are often a good choice for many tasks.