Instructions to use Talha/URDU-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Talha/URDU-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Talha/URDU-ASR")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Talha/URDU-ASR") model = AutoModelForCTC.from_pretrained("Talha/URDU-ASR") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61fab785def02b26e2a8742fdaeb9ca7de698cf7c43a725d245a1f1803196d85
- Size of remote file:
- 1.26 GB
- SHA256:
- 4b3bab8aaa03259b30c2759a955d4c338abb9ec90cf5fa0bc7839a5eb49cb83a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.