ictnlp / llama-omni

Seamless Speech Interaction with Large Language Models

  • Public
  • 58.3K runs
  • GitHub
  • Weights
  • Paper
  • License
Run with an API
Playground API Examples README Versions

Run time and cost

This model costs approximately $0.012 to run on Replicate, or 83 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia L40S GPU hardware. Predictions typically complete within 12 seconds.

Readme

🦙🎧 LLaMA-Omni: Seamless Speech Interaction with Large Language Models

LLaMA-Omni is a speech-language model built upon Llama-3.1-8B-Instruct. It supports low-latency and high-quality speech interactions, simultaneously generating both text and speech responses based on speech instructions.

💡 Highlights

  • 💪 Built on Llama-3.1-8B-Instruct, ensuring high-quality responses.

  • 🚀 Low-latency speech interaction with a latency as low as 226ms.

  • 🎧 Simultaneous generation of both text and speech responses.

  • ♻️ Trained in less than 3 days using just 4 GPUs.

LICENSE

Our code is released under the Apache-2.0 License. Our model, as it is built on Llama 3.1, is required to comply with the Llama 3.1 License.

Acknowledgements

  • LLaVA: The codebase we built upon.
  • SLAM-LLM: We borrow some code about speech encoder and speech adaptor.

Citation

If you have any questions, please feel free to submit an issue or contact fangqingkai21b@ict.ac.cn.

If our work is useful for you, please cite as:

@article{fang-etal-2024-llama-omni,
  title={LLaMA-Omni: Seamless Speech Interaction with Large Language Models},
  author={Fang, Qingkai and Guo, Shoutao and Zhou, Yan and Ma, Zhengrui and Zhang, Shaolei and Feng, Yang},
  journal={arXiv preprint arXiv:2409.06666},
  year={2024}
}