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
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:96c665dba0f9958948a087fdd24c64cab22701c1efdd61c075989c41cc00e697
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size 966995080
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