Instructions to use Siyam/Dansk-wav2vec21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siyam/Dansk-wav2vec21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siyam/Dansk-wav2vec21")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Siyam/Dansk-wav2vec21") model = AutoModelForCTC.from_pretrained("Siyam/Dansk-wav2vec21") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1d36134091841acd3ebe204de22ec6bc7e83269566ff65b40797a382119c063b
- Size of remote file:
- 2.8 kB
- SHA256:
- 4b47671e26a9b87c5d5152834d9c0fdfb73bedcf664dcfc3cf01523a09f51f1f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.