We provide two types of pretrained model in WeNet to facilitate users with different requirements.
-
Checkpoint Model, the model trained and saved as checkpoint by WeNet python code, you can reproduce our published result with it, or you can use it as checkpoint to continue.
-
Runtime Model, you can directly use
runtime modelin our x86 or android runtime, theruntime modelis export by Pytorch JIT on thecheckpoint model. Two kinds of runtime models are provided:- x86, server model, typically big.
- android, on-device model, typically small and been quantized.
Here is a list of the pretrained models on different datasets. The model structure, model size, and download link are given.
| Datasets | Languages | Checkpoint Model | Runtime Model(x86) | Runtime Model(android) |
|---|---|---|---|---|
| aishell | CN | Conformer/174M/Download | U2 Transformer/127M/Download | U2 Transformer/38M/Download |
| aishell2 | CN | U2++ Conformer/187M/Download | U2 Transformer/130M/Download | U2 Transformer/39M/Download |
| gigaspeech | EN | U2++ Conformer/472M/Download | U2++ Conformer/507M/Download | U2++ Transformer/51M/Download |
| librispeech | EN | Conformer/481M/Download | U2++ Conformer/199M/Download | |
| multi_cn | CN | U2 Conformer/193M/Download | U2 Conformer/130M/Download | U2 Conformer/65M/Download |