您可以使用get_weights()嵌入层的方法来获得词嵌入（即，本质上，嵌入层的权重就是嵌入向量）：
# if you have access to the embedding layer explicitly
embeddings = emebdding_layer.get_weights()[0]
# or access the embedding layer through the constructed model
# first `0` refers to the position of embedding layer in the `model`
embeddings = model.layers[0].get_weights()[0]
# `embeddings` has a shape of (num_vocab, embedding_dim)
# `word_to_index` is a mapping (i.e. dict) from words to their index, e.g. `love`: 69
words_embeddings = {w:embeddings[idx] for w, idx in word_to_index.items()}
# Now you can use it like this for example
print(words_embeddings['love']) # possible output: [0.21, 0.56, ..., 0.65, 0.10]
602392714
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