Any-to-Any
Transformers
ONNX
Safetensors
English
Chinese
multimodal
audio
video
speech
streaming
full-duplex
long-video
custom-code
Instructions to use inclusionAI/Realtime-Venus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inclusionAI/Realtime-Venus with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inclusionAI/Realtime-Venus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update citation team attribution
Browse files- README.md +1 -1
- README_zh.md +1 -1
README.md
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@@ -634,7 +634,7 @@ If you find Realtime-Venus useful, please cite the technical report:
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```bibtex
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@article{zhao2026realtime,
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title={{Realtime-Venus}: A full-duplex interaction system with asynchronous delegation},
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author={{Venus Team
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journal={arXiv preprint arXiv:2609.13814},
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year={2026}
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}
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```bibtex
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@article{zhao2026realtime,
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title={{Realtime-Venus}: A full-duplex interaction system with asynchronous delegation},
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author={{Venus Team(Ant Group), Tsinghua University}},
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journal={arXiv preprint arXiv:2609.13814},
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year={2026}
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}
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README_zh.md
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@@ -555,7 +555,7 @@ print("Saved generated speech to output/audio_full_duplex.wav")
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```bibtex
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@article{zhao2026realtime,
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title={{Realtime-Venus}: A full-duplex interaction system with asynchronous delegation},
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author={{Venus Team
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journal={arXiv preprint arXiv:2609.13814},
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year={2026}
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}
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```bibtex
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@article{zhao2026realtime,
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title={{Realtime-Venus}: A full-duplex interaction system with asynchronous delegation},
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author={{Venus Team(Ant Group), Tsinghua University}},
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journal={arXiv preprint arXiv:2609.13814},
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year={2026}
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}
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