Audio Classification
Transformers
ONNX
Safetensors
English
dualturn_endpointing
feature-extraction
turn-taking
endpointing
end-of-turn
voice-activity-detection
voice-agents
conversation
speech
audio
mimi
dualturn
real-time
custom_code
Instructions to use anyreach-ai/dualturn-endpointing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anyreach-ai/dualturn-endpointing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anyreach-ai/dualturn-endpointing", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anyreach-ai/dualturn-endpointing", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 474 Bytes
62a5e06 36bb752 62a5e06 36bb752 62a5e06 36bb752 62a5e06 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"architectures": [
"DualTurnEndpointingModel"
],
"auto_map": {
"AutoConfig": "modeling_dualturn.DualTurnEndpointingConfig",
"AutoModel": "modeling_dualturn.DualTurnEndpointingModel"
},
"core_hidden": 256,
"core_layers": 2,
"d_head": 128,
"d_model": 256,
"feat_dim": 1024,
"fvad_dim": 8,
"hop_s": 0.08,
"mimi_model": "kyutai/mimi",
"model_type": "dualturn_endpointing",
"torch_dtype": "float32",
"transformers_version": "4.52.4"
}
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