Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Urdu
wav2vec2
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Instructions to use kingabzpro/wav2vec2-60-urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kingabzpro/wav2vec2-60-urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kingabzpro/wav2vec2-60-urdu")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kingabzpro/wav2vec2-60-urdu") model = AutoModelForCTC.from_pretrained("kingabzpro/wav2vec2-60-urdu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d95a02faf00b25f4a455e9009358cdccd2fc973ce47cb1beef821ed2194529f3
- Size of remote file:
- 378 MB
- SHA256:
- 0490dd503d5a25403c6dc5d7b2711d66173ffacde983afd6662fe461fc7dd9fa
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