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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from kingabzpro/wav2vec2-60-urdu: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/kingabzpro/wav2vec2-60-urdu/resolve/734958c6f7b8e53bfdef1a0aeee1e855a44c68d8/pytorch_model.bin
- Command line
-
hf download hf://kingabzpro/wav2vec2-60-urdu@734958c6f7b8e53bfdef1a0aeee1e855a44c68d8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kingabzpro/wav2vec2-60-urdu/resolve/734958c6f7b8e53bfdef1a0aeee1e855a44c68d8/pytorch_model.bin
378 MB
- Xet hash:
- 40c1e3e8b9d62225830acfef284d23eb12492584296dcbfb5a15e1afc2aca969
- Size of remote file:
- 378 MB
- SHA256:
- 834bb66e7ed8b33cb9858e8d94f13dfd741d0d31259957e27a91f69fdc180e55
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.