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:
- 64343130a2b5f05d4521338a9ea8760be68cc69b7d438604477255af714d8cc4
- Size of remote file:
- 1.26 GB
- SHA256:
- 3eb1167b6d301f201da515819ef0bfb697821a4db0e6d5b6dcb1ea2baa3f0aa6
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