Instructions to use ntnu-smil/whisper-large-v3-turbo-ami-1-merged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ntnu-smil/whisper-large-v3-turbo-ami-1-merged with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ntnu-smil/whisper-large-v3-turbo-ami-1-merged")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ntnu-smil/whisper-large-v3-turbo-ami-1-merged") model = AutoModelForSpeechSeq2Seq.from_pretrained("ntnu-smil/whisper-large-v3-turbo-ami-1-merged", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92f7a206d31887e5a291ab1877afc8c0935efa8e77f2594b75b4c1e057edcd8b
- Size of remote file:
- 1.62 GB
- SHA256:
- b1520e1ad8e62ec31f38bb503dfc6e2ba1dbc65484128dad23962866b288dfbf
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