Update README.md

README.md

@@ -217,7 +217,10 @@ and two feedforward layers with 4 sigmoid outputs for each frame input at the to
 ## NVIDIA NeMo
 
 To train, fine-tune or perform diarization with Sortformer, you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo)[6]. We recommend you install it after you've installed Cython and latest PyTorch version.
+
 ```
+apt-get update && apt-get install -y libsndfile1 ffmpeg
+pip install Cython packaging
 pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[asr]
 ```
 
@@ -230,8 +233,8 @@ The model is available for use in the NeMo Framework[6], and can be used as a pr
 ```python
 from nemo.collections.asr.models import SortformerEncLabelModel
 
-# load model
-diar_model = SortformerEncLabelModel.restore_from(restore_path="/path/to/diar_streaming_sortformer_4spk-v2", map_location=torch.device('cuda'), strict=False)
+# load model from Hugging Face model card directly (You need a Hugging Face token)
+diar_model = SortformerEncLabelModel.from_pretrained("nvidia/diar_sortformer_4spk-v1")
 
 # If you have a downloaded model in "/path/to/diar_streaming_sortformer_4spk-v2.nemo", load model from a downloaded file
 diar_model = SortformerEncLabelModel.restore_from(restore_path="/path/to/diar_streaming_sortformer_4spk-v2.nemo", map_location='cuda', strict=False)