Instructions to use davidggphy/whisper-small-dv-second with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davidggphy/whisper-small-dv-second with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="davidggphy/whisper-small-dv-second")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("davidggphy/whisper-small-dv-second") model = AutoModelForSpeechSeq2Seq.from_pretrained("davidggphy/whisper-small-dv-second", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 45a7a505aa41633008ac3bb0a34420d8f282b58bb4673d33167b0bb42e4bfca3
- Size of remote file:
- 4.22 kB
- SHA256:
- 11340dde9438e2f7aafa63b0087826a8c5ffd0a32f4c21cb546acf123f5a78ae
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