turn-detector
An open-weights language model for contextually-aware end-of-utterance (EOU) detection in voice AI applications. The model predicts whether a user has finished speaking based on the semantic content of their transcribed speech, providing a critical complement to voice activity detection (VAD) systems.
Params
130 M
Context
8,192
Downloads 30d
978 K
Likes
147
Download history
daily snapshots · 55 days
▲ 355 K in the last 30 days (56.9%)
978 K622 K
Aug 22Sep 1Sep 11Sep 20
978 K607 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.5 GB | 1.1 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- LlamaForCausalLM
- Parameters
- 130 M
- Tensor type
- F32
- Context length
- 8,192
- Vocabulary
- 49,154
- Layers / heads
- 30 / 9
- Licence
- other
- First seen on the Hub
- 2024-12-07
- Base model
- Qwen2.5-0.5B-Instruct
- Training datasets
- undisclosed
- Added to our catalog
- 2026-07-28
Family
Base model and the most-downloaded derivatives in the catalog.
Compare with any text-classification model