Instructions to use Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024-litert-fp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024-litert-fp with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024-litert-fp") transcriptions = asr_model.transcribe(["file.wav"]) - LiteRT
How to use Reza2kn/visualears-fastconformer-fa32m-streaming-bpe1024-litert-fp with LiteRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle