Audio Classification
Transformers
ONNX
Safetensors
Malay
English
end-of-turn-detection
turn-detection
semantic-vad
endpointing
voice-agent
livekit
whisper
telephony
Instructions to use Scicom-intl/semantic-vad-eot-whisper-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Scicom-intl/semantic-vad-eot-whisper-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Scicom-intl/semantic-vad-eot-whisper-base")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Scicom-intl/semantic-vad-eot-whisper-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 313 Bytes
bbdc3c1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"chunk_length": 8,
"dither": 0.0,
"feature_extractor_type": "WhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 128000,
"nb_max_frames": 800,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": false,
"sampling_rate": 16000
}
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