Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use akmalmasud96/xlsr-53-ur with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akmalmasud96/xlsr-53-ur with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="akmalmasud96/xlsr-53-ur")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("akmalmasud96/xlsr-53-ur") model = AutoModelForCTC.from_pretrained("akmalmasud96/xlsr-53-ur", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from akmalmasud96/xlsr-53-ur: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/akmalmasud96/xlsr-53-ur/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://akmalmasud96/xlsr-53-ur/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/akmalmasud96/xlsr-53-ur/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- e6155a509a4dd176f997646abe9237b69b773a6adc35e64102b4044906347f17
- Size of remote file:
- 1.26 GB
- SHA256:
- 214b44662105cde54b38d60b80a14b117c356b2b47c2768c9a965a4e5798be18
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