Instructions to use nrshoudi/HuBERT_Jibbali_lang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nrshoudi/HuBERT_Jibbali_lang with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nrshoudi/HuBERT_Jibbali_lang")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("nrshoudi/HuBERT_Jibbali_lang") model = AutoModelForCTC.from_pretrained("nrshoudi/HuBERT_Jibbali_lang", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b256d33a4bd755cf323bc005e2ab6ed15166449529d9104ed2ba799b9233146f
- Size of remote file:
- 4.6 kB
- SHA256:
- 6304f3c17299b352b176eac943fb7ae7e6dc2637ad5228c256662027a27a92ec
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