Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
Persian
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use m3hrdadfi/wav2vec2-large-xlsr-persian-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/wav2vec2-large-xlsr-persian-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="m3hrdadfi/wav2vec2-large-xlsr-persian-v3")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("m3hrdadfi/wav2vec2-large-xlsr-persian-v3") model = AutoModelForCTC.from_pretrained("m3hrdadfi/wav2vec2-large-xlsr-persian-v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ffe743603bea8f6f355ea5ed42732669300a8ed6ea3c79d495fd03c5e6b1847
- Size of remote file:
- 1.26 GB
- SHA256:
- d6d33fc8e01332e2e4cf0230c159f63d02620a0528c19c69c3ce7d58777223e2
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