Use proxy sentences from cleaned data
That sounds like a reasonable solution. If you have access to data that is similar to your cleaned data you could get average sentence length from that data set. Otherwise, you could find other data in the language you are working with (from wikipedia or another source) and get average sentence length from there.
Of course your output vectors will not be as reliable as if you had the correct sentence boundaries, but it sounds like word order was preserved so there shouldn't be too much noise from incorrect sentence boundaries.
Gensim's Word2Vec model takes as an  input a list of lists with the inner list containing individual tokens/words of a sentence. As I understand Word2Vec is used to "quantify" the context of words within a text using vectors. 
I am currently dealing with a corpus of text that has already been split into individual tokens and no longer contains an obvious sentence format (punctuation has been removed). I was wondering how should I input this into the Word2Vec model? 
Say if I simply split the corpus into "sentences" of uniform length (10 tokens per sentence for example), would this be a good way of inputting the data into the model? 
Essentially, I am wondering how the format of the input sentences (list of lists) affects the output of Word2Vec?