Update README.md

README.md

@@ -39,7 +39,6 @@ segmentation_model = SegmentationModel().from_pretrained('diarizers-community/sp
 To use it within a pyannote speaker diarization pipeline, load the [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) pipeline, and convert the model to a pyannote compatible format: 
 
 ```python
-
 from pyannote.audio import Pipeline
 import torch
 
@@ -58,6 +57,7 @@ pipeline._segmentation.model = model.to(device)
 You can now use the pipeline on audio examples: 
 
 ```python
+from datasets import load_dataset
 # load dataset example
 dataset = load_dataset("diarizers-community/callhome", "spa", split="data")
 sample = dataset[0]["audio"]