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:
- 9a7e7d35bc3ef1a2780d32d18dc07549e8e47febe16b201540e063a196be9b9f
- Size of remote file:
- 967 MB
- SHA256:
- b3bc7e4465c8207bd92125d286d762b8b892b81bd76d06e1cf9e5d54a628915c
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