Automatic Speech Recognition
Transformers
PyTorch
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ptah23/whisper-tiny-en-US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ptah23/whisper-tiny-en-US with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ptah23/whisper-tiny-en-US")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ptah23/whisper-tiny-en-US") model = AutoModelForSpeechSeq2Seq.from_pretrained("ptah23/whisper-tiny-en-US") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b150103345138f2913fce8c7e4eff57e7b6e5e813aafad3d5c041a64c49e685a
- Size of remote file:
- 151 MB
- SHA256:
- 2d07d121916716b85d537c6cda6dba57bdedc74319ac149cf4f2f405121fdd49
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