Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
pa-IN
robust-speech-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1") model = AutoModelForCTC.from_pretrained("DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73cee73924046415ef32f01d07c9b618762e4e80267926839cac93b1b1de170f
- Size of remote file:
- 2.99 kB
- SHA256:
- 6b1aedc4fe7ec92200eafc3ebd49f8423ed1f76a39299859626edb51c651c948
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