Instructions to use oyvindgrutle/amk-whisper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oyvindgrutle/amk-whisper with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oyvindgrutle/amk-whisper")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("oyvindgrutle/amk-whisper") model = AutoModelForSpeechSeq2Seq.from_pretrained("oyvindgrutle/amk-whisper", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e8139ddba3f9c6208be3e4e6d9aaf93d9e127db825f62bbf898c836725f70fa
- Size of remote file:
- 6.17 GB
- SHA256:
- f882f67e203069a5722c7caf8f68b5a26a8657f53832f500fe25c36671347be3
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