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
| { | |
| "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 | |
| } | |