Instructions to use Siyong/MC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siyong/MC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siyong/MC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Siyong/MC") model = AutoModelForCTC.from_pretrained("Siyong/MC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ceedec88559b13126b26fbdc1e3acccf97c2fd69e9b350ab39fa871447d2575f
- Size of remote file:
- 378 MB
- SHA256:
- c285f387c86b46a92d6f8161b821f86b755bad00fb39755aff613b0d6e42dc2e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.