Update README.md

README.md

@@ -157,6 +157,11 @@ pip install nemo_toolkit['all']
 
 The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
 
+## Deployment in Production
+
+This model can be efficiently deployed with [NVIDIA Riva](https://developer.nvidia.com/riva) on premises of with cloud providers.
+Additionally, RIVA includes Conformer models trained on proprietary data in addition to the public one used in this checkpoint.
+
 ### Automatically instantiate the model
 
 ```python
@@ -190,11 +195,6 @@ This model accepts 16000 KHz Mono-channel Audio (wav files) as input.
 
 This model provides transcribed speech as a string for a given audio sample.
 
-## Production Deployment
-
-This model can be efficiently deployed with [NVIDIA Riva](https://developer.nvidia.com/riva) on prem or with most popular cloud providers.
-
-
 ## Model Architecture
 
 Conformer-CTC model is a non-autoregressive variant of Conformer model [1] for Automatic Speech Recognition which uses CTC loss/decoding instead of Transducer. You may find more info on the detail of this model here: [Conformer-CTC Model](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/models.html).