Text Classification
Transformers
ONNX
Safetensors
llama
text-generation
voice-ai
turn-detection
end-of-utterance
end-of-turn
conversational-ai
livekit
quantized
knowledge-distillation
text-embeddings-inference
Instructions to use livekit/turn-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use livekit/turn-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="livekit/turn-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("livekit/turn-detector") model = AutoModelForCausalLM.from_pretrained("livekit/turn-detector", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download generation_config.json from livekit/turn-detector: direct link, hf CLI and curl.
- Browser
- Download file 111 Bytes
-
https://huggingface.co/livekit/turn-detector/resolve/main/generation_config.json
- Command line
-
hf download hf://livekit/turn-detector/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/livekit/turn-detector/resolve/main/generation_config.json
111 Bytes
| { | |
| "_from_model_config": true, | |
| "bos_token_id": 0, | |
| "eos_token_id": 0, | |
| "transformers_version": "4.46.3" | |
| } | |