context2vec is a toolkit that represents sentential contexts of target words, as well as target words themselves, as low dimensional continuous vectors, commonly called embeddings. It is described in the following paper:
context2vec: Learning Generic Context Embedding with Bidirectional LSTM. Oren Melamud, Jacob Goldberger, Ido Dagan. CoNLL, 2016 [pdf].
The source code is available [here].