diff --git a/deeppavlov/models/embedders/transformers_embedder.py b/deeppavlov/models/embedders/transformers_embedder.py
index 6a1fd40d6c..7127d5ab86 100644
--- a/deeppavlov/models/embedders/transformers_embedder.py
+++ b/deeppavlov/models/embedders/transformers_embedder.py
@@ -63,7 +63,7 @@ def __call__(self, subtoken_ids_batch: Collection[Collection[int]], startofwords
         Args:
             subtoken_ids_batch: padded indexes for every subtoken
             startofwords_batch: a mask matrix with ``1`` for every first subtoken init in a token and ``0``
-             for every other subtoken
+                for every other subtoken
             attention_batch: a mask matrix with ``1`` for every significant subtoken and ``0`` for paddings
         """
         ids_tensor = torch.tensor(subtoken_ids_batch, device=self.device)
diff --git a/docs/features/models/bert.rst b/docs/features/models/bert.rst
index 3e27482b49..e90af2c6fd 100644
--- a/docs/features/models/bert.rst
+++ b/docs/features/models/bert.rst
@@ -7,7 +7,7 @@ English.
 | BERT paper: https://arxiv.org/abs/1810.04805
 | Google Research BERT repository: https://github.com/google-research/bert
 
-There are several pre-trained BERT models released by Google Research, more detail about these pretrained models could be found here: https://github.com/google-research/bert#pre-trained-models
+There are several pre-trained BERT models released by Google Research, more details about these pre-trained models could be found here: https://github.com/google-research/bert#pre-trained-models
 
 -  BERT-base, English, cased, 12-layer, 768-hidden, 12-heads, 110M parameters: download from `[google] <https://storage.googleapis.com/bert_models/2018_10_18/cased_L-12_H-768_A-12.zip>`__,
    `[deeppavlov] <http://files.deeppavlov.ai/deeppavlov_data/bert/cased_L-12_H-768_A-12.zip>`__
diff --git a/docs/features/models/squad.rst b/docs/features/models/squad.rst
index 5d58394875..995ada56ac 100644
--- a/docs/features/models/squad.rst
+++ b/docs/features/models/squad.rst
@@ -228,8 +228,7 @@ Pretrained models are available and can be downloaded:
 .. code:: bash
 
     python -m deeppavlov download deeppavlov/configs/squad/squad_zh_bert.json
-	
-	python -m deeppavlov download deeppavlov/configs/squad/squad_zh_zh_bert.json
+    python -m deeppavlov download deeppavlov/configs/squad/squad_zh_zh_bert.json
 	
 Link to DRCD dataset: http://files.deeppavlov.ai/datasets/DRCD.tar.gz
 Link to DRCD paper: https://arxiv.org/abs/1806.00920
diff --git a/docs/features/models/syntaxparser.rst b/docs/features/models/syntaxparser.rst
index 7e3edffea0..b08ce2ffb7 100644
--- a/docs/features/models/syntaxparser.rst
+++ b/docs/features/models/syntaxparser.rst
@@ -167,4 +167,4 @@ and dependency head.
 .. _`UD Pipe Future`: https://github.com/CoNLL-UD-2018/UDPipe-Future
 .. _`UDify (multilingual BERT)`: https://github.com/hyperparticle/udify
 
-So our model is by a valuable margin the state-of-the-art system for Russian syntactic parsing.
+So our model is the state-of-the-art system for Russian syntactic parsing by a valuable margin.