Instructions to use Soupis/SmallA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Soupis/SmallA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Soupis/SmallA")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Soupis/SmallA") model = AutoModelForSpeechSeq2Seq.from_pretrained("Soupis/SmallA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a6c8b50bfcf99fd78205085db5debbc4943bf7a083f19d42b4d460998dc92d4
- Size of remote file:
- 5.3 kB
- SHA256:
- 2d191c6d6a718e5b52276b4dc394e3d0fab9769ab5cd92b63a793e2e465c27db
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