Voice Activity Detection
Transformers
Safetensors
nemotron3_diarization
audio-frame-classification
speaker-diarization
streaming-sortformer
nemotron
medical
Instructions to use Aduomas/nemotron-3-diarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aduomas/nemotron-3-diarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("Aduomas/nemotron-3-diarization") model = AutoModelForAudioFrameClassification.from_pretrained("Aduomas/nemotron-3-diarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 623 Bytes
9ded405 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"feature_extractor": {
"feature_extractor_type": "NemotronAsrStreamingFeatureExtractor",
"feature_size": 128,
"hop_length": 160,
"n_fft": 512,
"padding_side": "right",
"padding_value": 0.0,
"preemphasis": 0.97,
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400
},
"processor_class": "Nemotron3DiarizationProcessor",
"streaming_mode": "low_latency",
"streaming_modes": {
"low_latency": [
9,
4
],
"ultra_low_latency": [
3,
1
],
"very_low_latency": [
6,
2
]
},
"subsampling_factor": 8
}
|