Automatic Speech Recognition
NeMo
Persian
speech
persian
farsi
fastconformer
ctc
streaming
on-device
shenava
shenava-1
visualears
rnnt
distillation
Instructions to use PersianML/Shenava-Rizeh-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use PersianML/Shenava-Rizeh-v1.0 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("PersianML/Shenava-Rizeh-v1.0") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f56ceac03ac79ad5d75d53f0965dbf72c836332dd589441db2c4582dc46949e8
- Size of remote file:
- 127 MB
- SHA256:
- 9b5973bde20f766d83045d19fe6b3ec300b3e8e76cc8e4728d02695acdce5860
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