Instructions to use Shubham09/Lisa_Whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/Lisa_Whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shubham09/Lisa_Whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shubham09/Lisa_Whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shubham09/Lisa_Whisper") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1acaaec62ec753e2b8a40903af867e7400ef77268448bf73af6799ee8ba15026
- Size of remote file:
- 290 MB
- SHA256:
- 08e42b612a6ae326dcaf673232af99ed9d64f997ea2aa87154c15da3d5d34ab9
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