Instructions to use hr16/PhoWhisper-base-flax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hr16/PhoWhisper-base-flax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hr16/PhoWhisper-base-flax")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hr16/PhoWhisper-base-flax") model = AutoModelForSpeechSeq2Seq.from_pretrained("hr16/PhoWhisper-base-flax") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e42a49fc62148008bdb73f044214ab4badd812f73ca9aef2efe40de076daa53
- Size of remote file:
- 290 MB
- SHA256:
- 2fe176fde811d6c86a44976be949a61a42139411d7822aa51dcd47106bef9483
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