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:
- 58ec9f81f321e773f269867ffbedf8a14bfd5a667edd37b66ec980de325a15b8
- Size of remote file:
- 13 MB
- SHA256:
- 59d5375d484602ef75137633303a63e501c91a49141381651b605a2e9d85ce45
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