Instructions to use rashmi035/whisper-tiny-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rashmi035/whisper-tiny-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rashmi035/whisper-tiny-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("rashmi035/whisper-tiny-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("rashmi035/whisper-tiny-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f0eb36b6150433b84f41ef42f8348fa4d7b1f54616b81808573ae505dd7e99a
- Size of remote file:
- 151 MB
- SHA256:
- f564d7ed3e69b4fb24c9494d830ba7a8783a263b726934cdb984ea93b371cc08
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