Instructions to use primeline/distil-whisper-large-v3-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use primeline/distil-whisper-large-v3-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="primeline/distil-whisper-large-v3-german")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("primeline/distil-whisper-large-v3-german") model = AutoModelForMultimodalLM.from_pretrained("primeline/distil-whisper-large-v3-german") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- da2c1e38e66af9dabb29dc3e2a6eb5d0a05965eaa315c69d3a11ac70375e06e2
- Size of remote file:
- 1.51 GB
- SHA256:
- d28a4e4d748101de5fdb20c95f16a794ca4454fad7c46ec365fec16b71abcd5e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.