Update README.md

README.md

@@ -130,7 +130,10 @@ 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)[5]. 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]
 ```
 
@@ -143,10 +146,14 @@ The model is available for use in the NeMo Framework[5], and can be used as a pr
 ```python
 from nemo.collections.asr.models import SortformerEncLabelModel
 
-# load model from a downloaded file
-diar_model = SortformerEncLabelModel.restore_from(restore_path="/path/to/diar_sortformer_4spk-v1.nemo", 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_sortformer_4spk-v1.nemo", load model from a downloaded file
+import torch
+diar_model = SortformerEncLabelModel.restore_from(restore_path="/path/to/diar_sortformer_4spk-v1.nemo", map_location=torch.device('cuda'), strict=False)
+
+
 # switch to inference mode
 diar_model.eval()
 ```