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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1445c8ec7d2123988923cae8409a679df19e095d21740d225769a540884b1897
- Size of remote file:
- 2.8 kB
- SHA256:
- 4b307c9b2db28c4bd98caf1c6e3f90e134bed850525cecf08f4ccec63b1cb731
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