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livekit/turn-detector - GGUF

This repo contains GGUF format model files for livekit/turn-detector.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.

Prompt template

<|im_start|><|system|>{system_prompt}<|im_end|><|im_start|><|user|>{prompt}<|im_end|>

Model file specification

Filename Quant type File Size Description
turn-detector-Q2_K.gguf Q2_K 0.088 GB smallest, significant quality loss - not recommended for most purposes
turn-detector-Q3_K_S.gguf Q3_K_S 0.088 GB very small, high quality loss
turn-detector-Q3_K_M.gguf Q3_K_M 0.094 GB very small, high quality loss
turn-detector-Q3_K_L.gguf Q3_K_L 0.098 GB small, substantial quality loss
turn-detector-Q4_0.gguf Q4_0 0.092 GB legacy; small, very high quality loss - prefer using Q3_K_M
turn-detector-Q4_K_S.gguf Q4_K_S 0.102 GB small, greater quality loss
turn-detector-Q4_K_M.gguf Q4_K_M 0.105 GB medium, balanced quality - recommended
turn-detector-Q5_0.gguf Q5_0 0.105 GB legacy; medium, balanced quality - prefer using Q4_K_M
turn-detector-Q5_K_S.gguf Q5_K_S 0.110 GB large, low quality loss - recommended
turn-detector-Q5_K_M.gguf Q5_K_M 0.112 GB large, very low quality loss - recommended
turn-detector-Q6_K.gguf Q6_K 0.138 GB very large, extremely low quality loss
turn-detector-Q8_0.gguf Q8_0 0.145 GB very large, extremely low quality loss - not recommended

Downloading instruction

Command line

Firstly, install Huggingface Client

pip install -U "huggingface_hub[cli]"

Then, downoad the individual model file the a local directory

huggingface-cli download tensorblock/turn-detector-GGUF --include "turn-detector-Q2_K.gguf" --local-dir MY_LOCAL_DIR

If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:

huggingface-cli download tensorblock/turn-detector-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
Downloads last month
67
GGUF
Model size
135M params
Architecture
llama

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Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for tensorblock/turn-detector-GGUF

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