biomedical word embeddings

I have around 93 million biomedical sentences, after performing some operation on these sentences word embeddings have to be created. I am looking for atleast 5 different word embeddings to be created from this sentences using any of the python libraries gensim, fasttext etc. some of the algorithms that I have in mind is skip-gram, cbow, fasttext, glove,etc next once these embeddings have been created it needs to be analyzed using spearman correlation analysis including one more trained word embedding that I will provide, finally some visualization has to be done from these word embeddings using t-sne or any other algorith to show how words are located in the vector space.