Instructions to use AlexanderMaz/LanguageModel_Fusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use AlexanderMaz/LanguageModel_Fusion with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("AlexanderMaz/LanguageModel_Fusion") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e36df94cbd1ee200f50b98792f15fef3ae75d19561c3dd28cad8c16c1416ddf1
- Size of remote file:
- 3.47 MB
- SHA256:
- 41ea43f5a397c28758dda07f490df575f21f80287c5da69526ea001f04744816
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.