Instructions to use oyvindgrutle/whisper-medium-amksim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyvindgrutle/whisper-medium-amksim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oyvindgrutle/whisper-medium-amksim")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("oyvindgrutle/whisper-medium-amksim") model = AutoModelForSpeechSeq2Seq.from_pretrained("oyvindgrutle/whisper-medium-amksim") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cb39173b5ee486705ccf4924096e1531bea49f6b9e5ed80e8199591751c29ff
- Size of remote file:
- 3.5 kB
- SHA256:
- 327fa7dea010d556b3353a813e8e85a931f57bcc231b78b7741355aeabb4f3c2
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