Instructions to use glenn2/whisper-small-b4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glenn2/whisper-small-b4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="glenn2/whisper-small-b4")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("glenn2/whisper-small-b4") model = AutoModelForMultimodalLM.from_pretrained("glenn2/whisper-small-b4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 304d1122daf531592687698414b2240412e83db67b1bf169b9201f7cae8096dd
- Size of remote file:
- 967 MB
- SHA256:
- ba71edbf676225ce1c5153fc8395d2695c08caeb7a86e9d0d42808326ff752f6
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