Automatic Speech Recognition
NeMo
Persian
speech
persian
farsi
fastconformer
ctc
streaming
on-device
shenava
shenava-1
visualears
distillation
Instructions to use PersianML/Shenava-Rizeh-Pizeh-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use PersianML/Shenava-Rizeh-Pizeh-v1.0 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("PersianML/Shenava-Rizeh-Pizeh-v1.0") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2fb6540c4019154c7a7c0ba3eabf9e0612dfaf5c26aa40fa6db4530d64762378
- Size of remote file:
- 27.5 MB
- SHA256:
- 5b434da8a1640a4ec4d3f3946902d751090e78c64b81246dba39166cd90832b6
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