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:
- 2d7dd1a37ceac0de76f1dcf34d29eb13129dab791f5591e6fce25cccb9f18054
- Size of remote file:
- 4.09 kB
- SHA256:
- 00cdd12c757b62e33aef471f1d29cc0023533cecc1374cd7688b877a0af8ef6e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.