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")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("livekit/turn-detector") model = AutoModelForCausalLM.from_pretrained("livekit/turn-detector") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 3,915 Bytes
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