Description

Add a ReadMe file in the GitHub folder.
Explain usage of the Templates

Other Comments

Principles of NLP Documentation
Each landing page at the folder level should have a ReadMe which explains -
○ Summary of what this folder offers.
○ Why and how it benefits users
○ As applicable - Documentation of using it, brief description etc
Scenarios folder:
○

I have some values in slots that are surrounded by curly braces and are meant to be returned as is. Instead, the trailing brace is being stripped. "${website}" becomes "${website". I have training examples where the whole "${website}" is included. Is there a way to change this behavior?

If I have a word, how do i get top k words closest to that given word. As far as i understand, there is a way to get it from cpp code but I can't find anything in the python library.
Something similar to what gensim word2vec implementation has:

model.most_similar(positive=[your_word_vector], topn=1))

This is also on page 356.

from nltk.corpus import sentiwordnet as swn

good = swn.senti_synsets('good', 'n')[0]
Traceback (most recent call last):
File "", line 1, in
TypeError: 'filter' object is not subscriptable

As Simple Transformers grows, the single page README documentation has gotten quite bloated and difficult to use. Because of this, I've decided that it's time (if not a little late already) to move the documentation to a more user-friendly Github Pages hosted website at the link below.

https://thilinarajapakse.github.io/simpletransformers/

As of now, only the text classification section is

Traceback (most recent call last):

File "", line 1, in
runfile('D:/nlp-tutorial/neural-machine-translation/nmt/train.py', wdir='D:/nlp-tutorial/neural-machine-translation/nmt')

File "C:\ProgramData\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)

File "C:\Prog

我觉得这里的else：row.append(i + vocab_size)应该改为else：row.append(i + train_size+vocab_size)，对吗？
这段代码是为doc节点和word节点生成稀疏邻接矩阵的代码，邻接矩阵的大小为train_size + vocab_size + test_size， 当doc文本序号i大于train_size时，剩下的不就是test_size大小的文本与单词建立连接吗？test_size在邻接矩阵之前不是有train_size+vocab_size，所以此时是不是文本从train_size+vocab_size开始一一与词建立连接？

以下为源码：

for i in range(len(shuffle_doc_words_list)):
    doc_words = shuffle_doc_words_

OS: MacOS 10.13.3
I installed the MeTA as instructed on setup guide. When I do the unit test

describe [ranker regression]
libc++abi.dylib: terminating with uncaught exception of type meta::corpus::corpus_exception: corpus configuration file (../data//cranfield/line.toml) not present

(tensorflow) F:\Postgraduate\KaggleLearning\multi-class-text-classification-cnn-rnn-master\multi-class-text-classification-cnn-rnn-master>python predict.py ./t
rained_results_1541818386/ ./data2/samples.csv
D:\Anaconda\anaconda\envs\tensorflow\lib\site-packages\gensim\utils.py:1212: UserWarning: detected Windows; aliasing chunkize to chunkize_serial
warnings.warn("detected Windows; aliasing c