Update README.md

README.md

@@ -18,7 +18,7 @@ tags:
 
 In order to prepare, adjust, or experiment with the model, it's necessary to install [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo) [1].
 We advise installing it once you've installed the most recent version of PyTorch.
-This model is trained on NVIDIA GeForce RTX 2070:
+This model is trained on NVIDIA GeForce RTX 2070:\
 Python 3.7.15\
 NumPy 1.21.6\
 PyTorch 1.21.1\
@@ -53,7 +53,7 @@ python3 transcribe_speech.py model_path=stt_kz_quartznet15x5.nemo dataset_manife
 
 ## Input and Output
 
-This model can take input from mono-channel audio .WAV files with a sample rate of 16,000 KHz. 
+This model can take input from mono-channel audio .WAV files with a sample rate of 16,000 KHz.\ 
 Then, this model gives you the spoken words in a text format for a given audio sample.
 
 ## Model Architecture
@@ -72,8 +72,8 @@ Average WER: 15.53%
 
 ## Limitations
 
-Because the GPU has limited power, we used a lightweight model architecture for fine-tuning. 
-In general, this makes it faster for inference but might show less overall performance. 
+Because the GPU has limited power, we used a lightweight model architecture for fine-tuning.\ 
+In general, this makes it faster for inference but might show less overall performance.\
 In addition, if the speech includes technical terms or dialect words the model hasn't learned, it may not work as well.
 
 ## References