Instructions to use Zaafir/urdu-asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zaafir/urdu-asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Zaafir/urdu-asr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Zaafir/urdu-asr") model = AutoModelForCTC.from_pretrained("Zaafir/urdu-asr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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- generated_from_trainer
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datasets:
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- common_voice
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model-index:
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- name: urdu-asr
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results: []
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- generated_from_trainer
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datasets:
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- common_voice
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base_model: facebook/wav2vec2-xls-r-300m
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model-index:
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- name: urdu-asr
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results: []
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