Instructions to use denden/iloko_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use denden/iloko_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="denden/iloko_model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("denden/iloko_model") model = AutoModelForCTC.from_pretrained("denden/iloko_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29d7758dc04fc11f281ecc6472a4f7ed1c9db83849a13034d65505cbedcea552
- Size of remote file:
- 1.26 GB
- SHA256:
- e0628a7a8afe85836c4e0b9283251558aefbf36ecd6ee284ac8f6410c2f9910c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.