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Apart from Seamless-M4T large (2.3B) and medium (1.2B) models, we are also releasing a small model (281M) targeted for on-device inference. To learn more about the usage and model details check out [README here](https://github.com/facebookresearch/seamless_communication/blob/main/docs/m4t/on_device_README.md)
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## Data
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-We open-source metadata for reconstructing the dataset we used for training our models. You can find the data and how to rebuild the dataset [here](data/seamless_communication/README.md).
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+We open-source metadata for reconstructing the dataset we used for training our models. You can find the data and how to rebuild the dataset [here](https://github.com/facebookresearch/seamless_communication/blob/main/docs/m4t/data_README.md).
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# Citation
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If you use SeamlessM4T in your work or any models/datasets/artifacts published in SeamlessM4T, please cite :
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Ning