Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use bgstud/whisper-small-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgstud/whisper-small-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bgstud/whisper-small-en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("bgstud/whisper-small-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("bgstud/whisper-small-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8cb962d79380b513a51409d41a40737b2d1a490838639056daf9be61120ca2dd
- Size of remote file:
- 3.5 kB
- SHA256:
- ec1ebd411876c4f81ebee7e680352cb85e69e6fbc8b0b320e8dda72b6064a07a
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