Instructions to use veract/veract-11-biov3.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use veract/veract-11-biov3.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="veract/veract-11-biov3.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("veract/veract-11-biov3.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("veract/veract-11-biov3.en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b96a2f02d9308a0795596ea7ab284cb5219f837b39ff9e2f9c3a8a517f0b039
- Size of remote file:
- 4.73 kB
- SHA256:
- 30a111173ce1922bd1a2c953d27ed70be5e4fbdf83571d0125272e43748e8b08
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.