Instructions to use Foxasdf/EnglishModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Foxasdf/EnglishModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Foxasdf/EnglishModel")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Foxasdf/EnglishModel") model = AutoModelForCTC.from_pretrained("Foxasdf/EnglishModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3898172d4f0ebf65d2db860b5f6911d277f02fb495bc91de2533d8544e4f8c8a
- Size of remote file:
- 1.26 GB
- SHA256:
- 4e515d973a34e8e21673d4e6b5b00d1d90a5c98b5fb97d171657e19c319194b0
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