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