Tutorials on training the Skip
2. Open and download the tensorflow version code.
unzip these files in the current folders.
(2). input the following code to the terminal:
the dataset used in skip_thoughts vectors is from [BookCorpus]: http://yknzhu.wixsite.com/mbweb
The, it's time to get the 2500# features now.
Now that, you have obtain the features of the input sentence. you can now load your texts to obtain the results. Come on ...
You can see the results of the algorithm as followings:
Do as the following links: https://github.com/tensorflow/models/tree/master/skip_thoughts
3. Encoding Sentences :
first, you should send a email to the auther of this paper and ask for the link of this dataset. Then you will download the following files:
(1). First, open a terminal and input "ipython" :
1. Send emails and download the training dataset.
For this moment, you already defined the environment, then, you need also do the followings:
Then, you will see the processing as follows:
[Attention] when you install the bazel, you need to install this software, but do not update it. Or, it may shown you some errors in the following operations.
Tutorials on training the Skip-thoughts vectors for features extraction of sentence.