Instructions to use Kghate/whisper-small-gn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kghate/whisper-small-gn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Kghate/whisper-small-gn")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Kghate/whisper-small-gn") model = AutoModelForSpeechSeq2Seq.from_pretrained("Kghate/whisper-small-gn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1294beacca3e3d4f963aefaf95b9c7e58a2874b1372ba66faf0341c3120e1b51
- Size of remote file:
- 4.73 kB
- SHA256:
- 8c8e63d33d59e6edbb4c1868f75df03dadb7c15c2a293e7da371edaf6d232db4
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