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:
- 16ccaa0d051406793df311013a5e4569862aba2da8c86ee1a57eba36f437055e
- Size of remote file:
- 4.22 kB
- SHA256:
- 9c4968d921ebc320a8ed35638c5be192a59b7a58d5ff9b3388770f524533fb8d
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