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:
- b94814d736b26a448b25569867017161ab56e7258dd8e1657c4c4642cb335dcf
- Size of remote file:
- 1.26 GB
- SHA256:
- 79119cea517eb3fcc571d3e27f7d09cba64de952f65943f6bbb55d7eea123f6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.