Instructions to use naot97/whisper-base-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use naot97/whisper-base-8bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="naot97/whisper-base-8bit")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("naot97/whisper-base-8bit") model = AutoModelForSpeechSeq2Seq.from_pretrained("naot97/whisper-base-8bit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd2ab82355df5127f851b1bd25e29fa3d2e8a3119770d05ab861465791ac8875
- Size of remote file:
- 102 MB
- SHA256:
- 63cea06d9be04a3a49a3ef5ea9b9ba3c291b5a41d91bf703d73b00a4eb341691
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