If you are looking for a pre-trained net for word-embeddings, I would suggest GloVe. The following blog from Keras is very informative of how to implement this. It also has a link to the pre-trained GloVe embeddings. There are pre-trained word vectors ranging from a 50 dimensional vector to 300 dimensional vectors. They were built on either Wikipedia, Common Crawl Data, or Twitter data. You can download them here: http://nlp.stanford.edu/projects/glove/. Additionally, you should examine the keras blog on how to implement them. https://blog.keras.io/using-pre-trained-word-embeddings-in-a-keras-model.html

If you are looking for a pre-trained net for word-embeddings, I would suggest GloVe. The following blog from Keras is very informative of how to implement this. It also has a link to the pre-trained GloVe embeddings. There are pre-trained word vectors ranging from a 50 dimensional vector to 300 dimensional vectors. They were built on either Wikipedia, Common Crawl Data, or Twitter data. You can download them here. Additionally, you should examine the keras blog on how to implement them.