Pretrained word embeddings vs model weights
Pre-trained word embedding methods such as word2vec, are used in NLP for the initialization of the first layer of a neural network before training for a new task. It is a single layer of weights (known as embeddings) and any prior knowledge from the word embeddings is only present in the first layer of the network, so the entire network would still need to be trained for a new target task.