# instantiate the pipeline
from pyannote.audio import Pipeline
from diarizers import SegmentationModel
from pyannote.audio import Pipeline
import torch

device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("cpu")

# diarizers를 통해 모델 로드
segmentation_model = SegmentationModel().from_pretrained('jaeyong2/speaker-segmentation-merged')
# pyannote 호환 형식으로 변환
model3 = segmentation_model.to_pyannote_model()

pipeline = Pipeline.from_pretrained(
  "pyannote/speaker-diarization-3.1",
  use_auth_token=<auth_token>)
pipeline._segmentation.model = model3

# run the pipeline on an audio file
diarization = pipeline("output.wav")

# dump the diarization output to disk using RTTM format
with open("audio.rttm", "w") as rttm:
    diarization.write_rttm(rttm)