Update vocab.get_vector docs to include features on Fasttext ngram (#4464)

* Update `vocab.get_vector`

* Added contrib agreement

.github/contributors/pberba.md

@@ -0,0 +1,106 @@
+# spaCy contributor agreement
+
+This spaCy Contributor Agreement (**"SCA"**) is based on the
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+
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+## Contributor Details
+
+| Field                          | Entry                |
+|------------------------------- | -------------------- |
+| Name                           | Pepe Berba           |
+| Company name (if applicable)   |                      |
+| Title or role (if applicable)  |                      |
+| Date                           | 2019-10-18           |
+| GitHub username                | pberba               |
+| Website (optional)             |                      |

spacy/vocab.pyx

@@ -337,6 +337,14 @@ cdef class Vocab:
         up by string or int ID. If no vectors data is loaded, ValueError is
         raised.
         
+        If `minn` is defined, then the resulting vector uses Fasttext's 
+        subword features by average over ngrams of `orth`.
+
+        orth (int / unicode): The hash value of a word, or its unicode string.
+        minn (int): Minimum n-gram length used for Fasttext's ngram computation. 
+            Defaults to the length of `orth`.
+        maxn (int): Maximum n-gram length used for Fasttext's ngram computation. 
+            Defaults to the length of `orth`.
         RETURNS (numpy.ndarray): A word vector. Size
             and shape determined by the `vocab.vectors` instance. Usually, a
             numpy ndarray of shape (300,) and dtype float32.

website/docs/api/vocab.md

@@ -168,15 +168,21 @@ cosines are calculated in minibatches, to reduce memory usage.
 Retrieve a vector for a word in the vocabulary. Words can be looked up by string
 or hash value. If no vectors data is loaded, a `ValueError` is raised.
 
+If `minn` is defined, then the resulting vector uses Fasttext's 
+subword features by average over ngrams of `orth`. (Introduced in spaCy `v2.1`)
+
 > #### Example
 >
 > ```python
 > nlp.vocab.get_vector("apple")
+> nlp.vocab.get_vector("apple", minn=1, maxn=5)
 > ```
 
 | Name        | Type                                     | Description                                                                                    |
-| ----------- | ---------------------------------------- | ----------------------------------------------------------------------------- |
+| ----------- | ---------------------------------------- | ---------------------------------------------------------------------------------------------- |
 | `orth`      | int / unicode                            | The hash value of a word, or its unicode string.                                               |
+| `minn`      | int                                      | Minimum n-gram length used for Fasttext's ngram computation. Defaults to the length of `orth`. |
+| `maxn`      | int                                      | Maximum n-gram length used for Fasttext's ngram computation. Defaults to the length of `orth`. |
 | **RETURNS** | `numpy.ndarray[ndim=1, dtype='float32']` | A word vector. Size and shape are determined by the `Vocab.vectors` instance.                  |
 
 ## Vocab.set_vector {#set_vector tag="method" new="2"}