How do I load FastText pretrained model with Gensim? I tried to load fastText pretrained model from here Fasttext model. I am using wiki.simple.en

from gensim.models.keyedvectors import KeyedVectors

word_vectors = KeyedVectors.load_word2vec_format('wiki.simple.bin', binary=True)


But, it shows the following errors

Traceback (most recent call last):
  File "nltk_check.py", line 28, in &lt;module&gt;
    word_vectors = KeyedVectors.load_word2vec_format('wiki.simple.bin', binary=True)
  File "P:\major_project\venv\lib\sitepackages\gensim\models\keyedvectors.py",line 206, in load_word2vec_format
     header = utils.to_unicode(fin.readline(), encoding=encoding)
  File "P:\major_project\venv\lib\site-packages\gensim\utils.py", line 235, in any2unicode
    return unicode(text, encoding, errors=errors)
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xba in position 0: invalid start byte


Question 1 How do I load fasttext model with Gensim? 

Question 2 Also, after loading the model, I want to find the similarity between two words 

 model.find_similarity('teacher', 'teaches')
 # Something like this
 Output : 0.99


How do I do this?
Here's the link for the methods available for fasttext implementation in gensim fasttext.py

from gensim.models.wrappers import FastText

model = FastText.load_fasttext_format('wiki.simple')

print(model.most_similar('teacher'))
# Output = [('headteacher', 0.8075869083404541), ('schoolteacher', 0.7955552339553833), ('teachers', 0.733420729637146), ('teaches', 0.6839243173599243), ('meacher', 0.6825737357139587), ('teach', 0.6285147070884705), ('taught', 0.6244685649871826), ('teaching', 0.6199781894683838), ('schoolmaster', 0.6037642955780029), ('lessons', 0.5812176465988159)]

print(model.similarity('teacher', 'teaches'))
# Output = 0.683924396754