parakeet-unified-en-0.6b

output = asr_model.transcribe([wav_file_path])
print(output[0].text)

from nemo.collections.asr.inference.factory.pipeline_builder import PipelineBuilder
from omegaconf import OmegaConf

# Path to the buffered rnnt config file downloaded from above link
cfg_path = 'buffered_rnnt.yaml'
cfg = OmegaConf.load(cfg_path)

# Pass the paths of all the audio files for inferencing
audios = ['/path/to/your/audio.wav']

# Create the pipeline object and run inference
pipeline = PipelineBuilder.build_pipeline(cfg)
output = pipeline.run(audios)

# Print the output
for entry in output:
  print(entry['text'])