Instructions to use thisiskeithkwan/cantomed11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thisiskeithkwan/cantomed11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thisiskeithkwan/cantomed11")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("thisiskeithkwan/cantomed11") model = AutoModelForSpeechSeq2Seq.from_pretrained("thisiskeithkwan/cantomed11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64fb4f63faee50236a2ae06fca363e11f354bda7056330b141884bde2ecf57f1
- Size of remote file:
- 3.06 GB
- SHA256:
- 398f09b12278684172438a0d9bd14c76eecca880695c42779c37e6bd99f151f9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.