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:
- e56f89209abb9411885f4eb83983e831fcd26c748500e48b2d7276f8e97a355b
- Size of remote file:
- 98.1 MB
- SHA256:
- c070a7e86925772e6eb6e5b99309ea8d65662a850d6fa2f66784477ef146056e
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