Instructions to use LBR47/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LBR47/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="LBR47/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("LBR47/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("LBR47/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b099d7b8954f23fa5e4aacb363fa8e9e4de8966e2ee21252a6a7d3bd1647a855
- Size of remote file:
- 4.08 kB
- SHA256:
- 8a87f6ea171d92578d02517346061bcc3edbad83f2aef242873a62014edf6b0c
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