Automatic Speech Recognition
Transformers
PyTorch
JAX
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use danurahul/wav2vec2-large-xlsr-pa-IN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danurahul/wav2vec2-large-xlsr-pa-IN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="danurahul/wav2vec2-large-xlsr-pa-IN")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("danurahul/wav2vec2-large-xlsr-pa-IN") model = AutoModelForCTC.from_pretrained("danurahul/wav2vec2-large-xlsr-pa-IN", device_map="auto") - Notebooks
- Google Colab
- Kaggle
README.md
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The script used for training can be found
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The Common Voice `train`, `validation` was used for training as well as validation and testing #
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The script used for training can be found https://github.com/rahul-art/huggingface_wav2vec2_punjabi/blob/main/Fine_Tune_XLSR_Wav2Vec2_on_Punjabi_ASR_with_%F0%9F%A4%97_Transformers.ipynb
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