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:
- 90d4981fb7cb8f35d1dd24d2c0f2b988e392b07ee6011e18565e7c5899820974
- Size of remote file:
- 967 MB
- SHA256:
- 682e8d4ee36b72f1b30932a5ca5c24a3f5d7ab7e5b3193b0b15f16229cfa4732
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