fix: typo spelling grammar (#13212)

* fix: typo spelling grammar

* fix: make fixup

docs/source/model_doc/deberta_v2.rst

@@ -53,7 +53,7 @@ New in v2:
   transformer layer to better learn the local dependency of input tokens.
 - **Sharing position projection matrix with content projection matrix in attention layer** Based on previous
   experiments, this can save parameters without affecting the performance.
-- **Apply bucket to encode relative postions** The DeBERTa-v2 model uses log bucket to encode relative positions
+- **Apply bucket to encode relative positions** The DeBERTa-v2 model uses log bucket to encode relative positions
   similar to T5.
 - **900M model & 1.5B model** Two additional model sizes are available: 900M and 1.5B, which significantly improves the
   performance of downstream tasks.

docs/source/model_doc/speech_to_text.rst

@@ -42,8 +42,8 @@ features. The :class:`~transformers.Speech2TextProcessor` wraps :class:`~transfo
 predicted token ids.
 
 The feature extractor depends on :obj:`torchaudio` and the tokenizer depends on :obj:`sentencepiece` so be sure to
-install those packages before running the examples. You could either install those as extra speech dependancies with
-``pip install transformers"[speech, sentencepiece]"`` or install the packages seperatly with ``pip install torchaudio
+install those packages before running the examples. You could either install those as extra speech dependencies with
+``pip install transformers"[speech, sentencepiece]"`` or install the packages seperately with ``pip install torchaudio
 sentencepiece``. Also ``torchaudio`` requires the development version of the `libsndfile
 <http://www.mega-nerd.com/libsndfile/>`__ package which can be installed via a system package manager. On Ubuntu it can
 be installed as follows: ``apt install libsndfile1-dev``