Model Details
Full Model IDlivekit/turn-detector
Pipeline / Tasktext-classification
Librarytransformers
Downloads (all-time)1.2M
Likes166
Last Modified2/11/2026
Author / Orglivekit
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-classification", model="livekit/turn-detector")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformersonnxsafetensorsllamatext-generationvoice-aiturn-detectionend-of-utteranceend-of-turnconversational-ailivekitquantizedknowledge-distillationtext-classificationenesfrdeitptnlzhjakoidtrruhibase_model:Qwen/Qwen2.5-0.5B-Instructbase_model:quantized:Qwen/Qwen2.5-0.5B-Instruct
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🏷️ Task: Text Classification
This model is designed for the Text Classification task. Explore more models for this use case.
All Text Classification Models →📊 Popularity
⬇ Downloads1.2M
❤️ Community Likes166
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.