Instructions to use espnet/xeus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use espnet/xeus with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "espnet/xeus" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Create meta.yaml
Browse files
meta.yaml
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espnet: '202304'
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files:
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s2t_model_file: model/xeus_checkpoint.pth
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python: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0]
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timestamp: 1690664683.078748
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torch: 1.13.1
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yaml_files:
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s2t_train_config: model/config.yaml
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