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
Ctrl+K
- Jan20_18-58-52_54f20cc19bfe
- Jan20_20-35-28_18132f059d04
- Jan20_21-04-33_18132f059d04
- Jan21_07-31-02_8de2030b21f4
- Jan21_09-10-19_8de2030b21f4
- Jan21_09-13-09_8de2030b21f4
- Jan21_10-57-49_f896580bb99d
- Jan21_12-53-12_f896580bb99d
- Jan21_14-26-50_c363f86c0f43
- Jan21_15-07-14_c363f86c0f43
- Jan21_15-42-45_c363f86c0f43
- Jan21_22-10-48_6cee47304eb8
- Jan21_22-30-19_6cee47304eb8
- Jan21_22-44-15_6cee47304eb8
- Jan21_23-00-49_6cee47304eb8