diff --git a/spacy/vectors.pyx b/spacy/vectors.pyx
index 72e30bd2f..0eec5a00a 100644
--- a/spacy/vectors.pyx
+++ b/spacy/vectors.pyx
@@ -90,6 +90,33 @@ cdef class Vectors:
     def most_similar(self, key):
         raise NotImplementedError
 
+    def from_glove(self, path):
+        '''Load GloVe vectors from a directory. Assumes binary format,
+        that the vocab is in a vocab.txt, and that vectors are named
+        vectors.{size}.[fd].bin, e.g. vectors.128.f.bin for 128d float32
+        vectors, vectors.300.d.bin for 300d float64 (double) vectors, etc.
+        By default GloVe outputs 64-bit vectors.'''
+        path = util.ensure_path(path)
+        for name in path.iterdir():
+            if name.parts[-1].startswith('vectors'):
+                _, dims, dtype, _2 = name.parts[-1].split('.')
+                self.width = int(dims)
+                break
+        else:
+            raise IOError("Expected file named e.g. vectors.128.f.bin")
+        bin_loc = path / 'vectors.{dims}.{dtype}.bin'.format(dims=dims,
+                                                             dtype=dtype)
+        with bin_loc.open('rb') as file_:
+            self.data = numpy.fromfile(file_, dtype='float64')
+            self.data = numpy.ascontiguousarray(self.data, dtype='float32')
+        n = 0
+        with (path / 'vocab.txt').open('r') as file_:
+            for line in file_:
+                self.add(line.strip())
+                n += 1
+        if (self.data.size % self.width) == 0:
+            self.data
+
     def to_disk(self, path, **exclude):
         serializers = OrderedDict((
             ('vectors', lambda p: numpy.save(p.open('wb'), self.data, allow_pickle=False)),