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
Training in progress, step 20
Browse files
preprocessor_config.json
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"hop_length": 160,
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pytorch_model.bin
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runs/Nov21_13-24-53_171bb1214519/1669039225.4930508/events.out.tfevents.1669039225.171bb1214519.79.1
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training_args.bin
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