Instructions to use mohammed/quantized-whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohammed/quantized-whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohammed/quantized-whisper-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohammed/quantized-whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohammed/quantized-whisper-small") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4bf4bc21ed10d2ce10b667a6d3e03bf842a726d95d751c7bfedf122393e13be
- Size of remote file:
- 195 MB
- SHA256:
- 8585c8ec6d8265666f5505ce2224cd1eecda44d38ef4c8e1a87946d56b9676d0
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