Instructions to use Foxasdf/EnglishModel_STT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Foxasdf/EnglishModel_STT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Foxasdf/EnglishModel_STT")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Foxasdf/EnglishModel_STT") model = AutoModelForCTC.from_pretrained("Foxasdf/EnglishModel_STT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b5af356307c13efd41953fc05f6bd98ae14b3ea3e197e57c315b80aec850af68
- Size of remote file:
- 1.26 GB
- SHA256:
- 10da426ed316395ef5ae21c226807bcc186751514c71044f9f84b195415f0575
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