This is a fine-tuned version of the LiveKit Turn Detector model, optimized for specific production use cases.
Model Description
Base Model: Qwen2-0.5B-Instruct
Task: End-of-Utterance (EOU) detection for voice agents
Format: ONNX (INT8 quantized)
Fine-tuning Method: LoRA (Low-Rank Adaptation)
Training Data: 1735 production conversation records
Performance
Accuracy: 79.25% @ threshold 0.38
Dataset: 1735 annotated production records
Improvement: +13.08% over LiveKit v1.2.2-en baseline
Usage
from livekit.agents import turn_detector
# Use with LiveKit agents
detector = turn_detector.EOUModel.load(
model_id="Vurtnec/turn-detector",
download_files=["model.onnx"]
)
Model Files
model.onnx: ONNX Runtime optimized model (250MB)
Tokenizer files: Standard Qwen2 tokenizer configuration