Update README.md

README.md

@@ -40,9 +40,9 @@ package can be installed by following the instructions outlined here: [Installat
 
 Once installed, a [`Translator`](https://github.com/fairinternal/seamless_communication/blob/590547965b343b590d15847a0aa25a6779fc3753/src/seamless_communication/models/inference/translator.py#L47) 
 object can be instantiated to perform all five of the spoken langauge tasks. The `Translator` is instantiated with three arguments:
-1. `model_name_or_card`: SeamlessM4T checkpoint. Can be either `multitask_unity_medium` for the medium model, or `multitask_unity_large` for the large model
-2. `vocoder_name_or_card`: vocoder checkpoint (`vocoder_36langs`)
-3. `device`: Torch device
+1. **model_name_or_card**: SeamlessM4T checkpoint. Can be either `seamlessM4T_medium` for the medium model, or `seamlessM4T_large` for the large model
+2. **vocoder_name_or_card**: vocoder checkpoint (`vocoder_36langs`)
+3. **device**: Torch device
 
 ```python
 import torch
@@ -50,7 +50,7 @@ from seamless_communication.models.inference import Translator
 
 
 # Initialize a Translator object with a multitask model, vocoder on the GPU.
-translator = Translator("multitask_unity_large", vocoder_name_or_card="vocoder_36langs", device=torch.device("cuda:0"))
+translator = Translator("seamlessM4T_large", vocoder_name_or_card="vocoder_36langs", device=torch.device("cuda:0"))
 ```
 
 Once instantiated, the `predict()` method can be used to run inference as many times on any of the supported tasks.