Update README.md

README.md

@@ -208,22 +208,22 @@ The model can be trained using this [example script](https://github.com/NVIDIA/N
 ### Evaluation
 
 To evaluate Sortformer diarizer and save diarization results in RTTM format, use the inference [example script](https://github.com/NVIDIA/NeMo/blob/main/examples/speaker_tasks/diarization/neural_diarizer/e2e_diarize_speech.py):
-```shell
+```bash
 python [NEMO_GIT_FOLDER]/examples/speaker_tasks/diarization/neural_diarizer/e2e_diarize_speech.py 
- model_path="/path/to/diar_sortformer_4spk-v1.nemo" 
- manifest_filepath="/path/to/multispeaker_manifest_with_reference_rttms.json"
- collar=COLLAR
+ model_path="/path/to/diar_sortformer_4spk-v1.nemo" \
+ manifest_filepath="/path/to/multispeaker_manifest_with_reference_rttms.json" \
+ collar=COLLAR \
  out_rttm_dir="/path/to/output_rttms"
 ```
 
 You can provide the post-processing YAML configs from [`post_processing` folder](https://github.com/NVIDIA/NeMo/tree/main/examples/speaker_tasks/diarization/conf/post_processing) to reproduce the optimized post-processing algorithm for each development dataset:
-```shell
-python [NEMO_GIT_FOLDER]/examples/speaker_tasks/diarization/neural_diarizer/e2e_diarize_speech.py 
- model_path="/path/to/diar_sortformer_4spk-v1.nemo" 
- manifest_filepath="/path/to/multispeaker_manifest_with_reference_rttms.json"
- collar=COLLAR
- bypass_postprocessing=False
- postprocessing_yaml="/path/to/postprocessing_config.yaml"
+```bash
+python [NEMO_GIT_FOLDER]/examples/speaker_tasks/diarization/neural_diarizer/e2e_diarize_speech.py \
+ model_path="/path/to/diar_sortformer_4spk-v1.nemo" \
+ manifest_filepath="/path/to/multispeaker_manifest_with_reference_rttms.json" \
+ collar=COLLAR \
+ bypass_postprocessing=False \
+ postprocessing_yaml="/path/to/postprocessing_config.yaml" \
  out_rttm_dir="/path/to/output_rttms"
 ```