Instructions to use billfass/fongbe_asr_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use billfass/fongbe_asr_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="billfass/fongbe_asr_model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("billfass/fongbe_asr_model") model = AutoModelForCTC.from_pretrained("billfass/fongbe_asr_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1efaf9fd98d0e378ebb109f388ae50fdc5eeab60233675c31daa3c7cc0f58b07
- Size of remote file:
- 1.26 GB
- SHA256:
- 896ad9e07a6484f2c6446d03f2b549ba1ed44b9ab0f977eb9af5eb0a84eff74b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.