Instructions to use Mubarak127/SALAMA_NEWMEDTT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mubarak127/SALAMA_NEWMEDTT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Mubarak127/SALAMA_NEWMEDTT")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Mubarak127/SALAMA_NEWMEDTT") model = AutoModelForSpeechSeq2Seq.from_pretrained("Mubarak127/SALAMA_NEWMEDTT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27bc38597450cbcb0cc6df06209a56ff59d08fc8a2c474a85a640da839ed5ab8
- Size of remote file:
- 4.92 kB
- SHA256:
- f479a945e272c1b0cbf1a4674fe26ba1fbbc8614dcac510d0291240bacaa3486
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