Instructions to use RetaSy/whisper-test-ar-tarteel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RetaSy/whisper-test-ar-tarteel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RetaSy/whisper-test-ar-tarteel")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("RetaSy/whisper-test-ar-tarteel") model = AutoModelForSpeechSeq2Seq.from_pretrained("RetaSy/whisper-test-ar-tarteel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1457c7a9d3fadff5b3dec2c82d73257ed07bbc761ab8ac9a9b98b23ccad654d
- Size of remote file:
- 3.64 kB
- SHA256:
- b325e0fb6a3b7557ae36bfe49271a8384987cdb0e4aafd06b4abc9062e894f66
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