anchor.diff:  Test expects a sequence of lines where line represeted as an array of words.
   You could use helper streamToLines
   *)
  -let testData = Input.FilePath("D:/ft/data/dbpedia.test")
  +let testData = Input.FilePath("./data/dbpedia.test")
   let r = Classifier.test(state, 1, FileReader.streamToLines testData)
   printfn "%A" r
   assert(r.precision >= 9.8f) 
  
positive.code: #r "NFastText.dll"
  open NFastText
  open NFastText.FileReader
  let trainData = Input.FilePath("D:/ft/data/dbpedia.train")
  //we train our classifier in 4 threads, using 2 wordgrams and default model args, verbosive, without pretrained vectors and with label prefix "__label__"
  let state = Classifier.train(trainData, 4, Classifier.args, 2uy, "__label__", true, None)
  
  
negative.code: ##Train
  Works almost the same as classification, but train files could be without line endings.
  *)
  let trainData = Input.FilePath("./data/text9")
  let skipgram = Vectorizer.train(trainData,4,Vectorizer.args,Args.VecModel.sg, 3uy, 6uy, true)
  (**
  ##Vectorization
  Expects as input a sequence of words and result is a sequence of tuples of words with associated vectors.
  *)
  let words = Input.FilePath("./data/queries.txt") |> FileReader.streamToWords
  let wrodsWithVectors = Vectorizer.getWordVectors(skipgram,words)
  
  (**
  