Update README.md

README.md

@@ -10,8 +10,8 @@ SeamlessM4T is designed to provide high quality translation, allowing people fro
 
 SeamlessM4T covers:
 - 📥 101 languages for speech input
-- ⌨️   96 Languages for text input/output
-- 🗣️  35 languages for speech output. 
+- ⌨️ 96 Languages for text input/output
+- 🗣️ 35 languages for speech output. 
 
 This unified model enables multiple tasks without relying on multiple separate models:
 - Speech-to-speech translation (S2ST)
@@ -23,13 +23,15 @@ This unified model enables multiple tasks without relying on multiple separate m
 ## SeamlessM4T models
 | Model Name | #params | checkpoint | metrics |
 | - | - | - | - |
-| SeamlessM4T-Large | 2.3B |[model]() | [metrics]() |
-| SeamlessM4T-Medium | 1.2B |[model]() | [metrics]() |
+| SeamlessM4T-Large | 2.3B |[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-large) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-large/resolve/main/multitask_unity_large.pt) | [metrics]() |
+| SeamlessM4T-Medium | 1.2B |[🤗 Model card](https://huggingface.co/facebook/seamless-m4t-medium) - [checkpoint](https://huggingface.co/facebook/seamless-m4t-medium/resolve/main/multitask_unity_medium.pt) | [metrics]() |
 
 We provide the extensive evaluation results of seamlessM4T-Large and SeamlessM4T-Medium reported in the paper (as averages) in the `metrics` files above.
 
 ## Instructions to run inference with SeamlessM4T models
 
+Install `seamless_communication` by following the instructions mentioned here: [Installation](https://github.com/fairinternal/seamless_communication/tree/main#installation)
+
 Inference calls for the `Translator` object instanciated with a Multitasking UnitY model with the options:
 - `multitask_unity_large`
 - `multitask_unity_medium`