Automatic Speech Recognition
Transformers
PyTorch
English
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Wishwa98/ASRForCommonVoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wishwa98/ASRForCommonVoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Wishwa98/ASRForCommonVoice")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Wishwa98/ASRForCommonVoice") model = AutoModelForSpeechSeq2Seq.from_pretrained("Wishwa98/ASRForCommonVoice") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2500
Browse files- pytorch_model.bin +1 -1
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