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livekit
/
turn-detector

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
Model card Files Files and versions
xet
Community
6

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
turn-detector
Ctrl+K
Ctrl+K
  • 2 contributors
History: 13 commits
yepher's picture
yepher
Update README.md
fba34c3 verified 3 months ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • LICENSE
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  • README.md
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  • added_tokens.json
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  • config.json
    793 Bytes
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  • generation_config.json
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  • merges.txt
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  • model.safetensors
    538 MB
    xet
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  • model_quantized.onnx
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    xet
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  • ort_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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