Instructions to use ImNobody/whisper-base-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ImNobody/whisper-base-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ImNobody/whisper-base-de")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ImNobody/whisper-base-de") model = AutoModelForSpeechSeq2Seq.from_pretrained("ImNobody/whisper-base-de") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 274fb4b1e3a1fd05294daadd2eeda5365bcd4037d86c6d57215820e645bb29c9
- Size of remote file:
- 290 MB
- SHA256:
- a2101111e17c4311c16d7625a089dafa9b0c20daf24a83e3c0fe7c8fd0129246
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