Instructions to use asafaya/hubert-large-arabic-transcribe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/hubert-large-arabic-transcribe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="asafaya/hubert-large-arabic-transcribe")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("asafaya/hubert-large-arabic-transcribe") model = AutoModel.from_pretrained("asafaya/hubert-large-arabic-transcribe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72aa14645297dfc0962a273c00f82ab29457aa7202b9bca11f28ca0e84d64b5e
- Size of remote file:
- 1.26 GB
- SHA256:
- e05705d7b9594d80f25f64d0e075d016cb1722adbd52ff7c52877af132e3d62f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.