In the current paper, we derive pre-trained contextual character embeddings from Flair's forwardbackward LM trained on a 1-billion word corpus of English (Chelba et al., 2014) , and observe if these embeddings yield the same large improvements for character-level tasks as yielded by pre-trained contextual word embeddings for word-level tasks.