Instructions to use esb/wav2vec2-ctc-pretrained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esb/wav2vec2-ctc-pretrained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="esb/wav2vec2-ctc-pretrained")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("esb/wav2vec2-ctc-pretrained") model = AutoModel.from_pretrained("esb/wav2vec2-ctc-pretrained") - Notebooks
- Google Colab
- Kaggle
File size: 135 Bytes
a341c6c | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:8fc4e342ff9241a5c26ac4a4d62714b182097a3889f9136fbed47ba4b493aff2
size 1261756878
|