Instructions to use abdouaziiz/wav2vec2-xls-r-300m-wolof-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdouaziiz/wav2vec2-xls-r-300m-wolof-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="abdouaziiz/wav2vec2-xls-r-300m-wolof-lm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("abdouaziiz/wav2vec2-xls-r-300m-wolof-lm") model = AutoModelForCTC.from_pretrained("abdouaziiz/wav2vec2-xls-r-300m-wolof-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 702a4843cba5e832c426b773c3445485ef2cc30c9a7cb7c3de071c561994ca5c
- Size of remote file:
- 4.02 MB
- SHA256:
- 789f6fb228a256be6da89c5d318a0b434b5cc58918b028b782c04dc90fbf96e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.