Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Urdu
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
sv
robust-speech-event
model_for_talk
hf-asr-leaderboard
Instructions to use Maniac/wav2vec2-xls-r-urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maniac/wav2vec2-xls-r-urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Maniac/wav2vec2-xls-r-urdu")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Maniac/wav2vec2-xls-r-urdu") model = AutoModelForCTC.from_pretrained("Maniac/wav2vec2-xls-r-urdu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e16ecc8dcfb1be6f75f4f291844b45428a10b0a8814883138d89806f5f743e0b
- Size of remote file:
- 2.99 kB
- SHA256:
- f0e764bedbce34050e8790d7b53d28adc314fc2eec7012bab818227199ae9348
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