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  | [![Model architecture](https://img.shields.io/badge/Model_Arch-Conformer--Transducer-lightgrey#model-badge)](#model-architecture)
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  | [![Model size](https://img.shields.io/badge/Params-120M-lightgrey#model-badge)](#model-architecture)
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- | [![Language](https://img.shields.io/badge/Language-rw-lightgrey#model-badge)](#datasets)
 
 
 
 
 
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  | [![Model architecture](https://img.shields.io/badge/Model_Arch-Conformer--Transducer-lightgrey#model-badge)](#model-architecture)
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  | [![Model size](https://img.shields.io/badge/Params-120M-lightgrey#model-badge)](#model-architecture)
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+ | [![Language](https://img.shields.io/badge/Language-ru-lightgrey#model-badge)](#datasets)
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+ This model transcribes speech into lowercase Cyrillic alphabet including space, and is trained on around 1500 hours of Russian speech data.
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+ It is a non-autoregressive "large" variant of Conformer, with around 120 million parameters.
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+ See the [model architecture](#model-architecture) section and [NeMo documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/models.html#conformer-transducer) for complete architecture details.