Instructions to use hr16/PhoWhisper-small-flax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hr16/PhoWhisper-small-flax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hr16/PhoWhisper-small-flax")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hr16/PhoWhisper-small-flax") model = AutoModelForSpeechSeq2Seq.from_pretrained("hr16/PhoWhisper-small-flax") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d911e030b26f0daef77e50fc7f338d2040d72da2c3edfc747698889cd5b5d0d
- Size of remote file:
- 967 MB
- SHA256:
- f1706e8d63fed7ba779769721df33df2c53e17709c5e982d8d7f5be77e2edcb6
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