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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2e86353530833285b5df99f03fd1f2536c8ef624ce6ce2aecc283cc62df5b49
- Size of remote file:
- 2.86 kB
- SHA256:
- 3ff20412246f17404ec160fa37357b302889cd7a7124d3a593b95d909dbd5223
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