In addition to the answer by @lewtun I would not recommend to get context-less embeddings this way. The whole point of context-sensitive models is that the representation depends on the context. The meaning of “floral” (and any word, basically) depends on its context. If you use these LMs in this way, I fear your output representation may not be as stable/good as you’d want.
If you are indeed looking for single word representations without context, it might be better to rely on context-free representations as per word2vec/GloVe embeddings.