Instructions to use basilkr/whisper_st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basilkr/whisper_st with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basilkr/whisper_st")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basilkr/whisper_st") model = AutoModelForSpeechSeq2Seq.from_pretrained("basilkr/whisper_st") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1faf8afb0f1456b53d35eaaeb5a912e432ebc042217d14d4ba265953428f74b6
- Size of remote file:
- 13.6 kB
- SHA256:
- cb4efdc45f0d3e9562a6a346b6d3e00be0c5acde5e75f4745a77600d4c9748c5
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