Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Arabic
wav2vec2
Generated from Trainer
Instructions to use Foxasdf/ArabicSpeechToText with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Foxasdf/ArabicSpeechToText with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Foxasdf/ArabicSpeechToText")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Foxasdf/ArabicSpeechToText") model = AutoModelForCTC.from_pretrained("Foxasdf/ArabicSpeechToText", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62bc5a281bbffb15bb117f9ae770667f76a2603d756f828415b9249a7f449942
- Size of remote file:
- 1.26 GB
- SHA256:
- 42d5ba24be745d2d33bf9a83a6171832a8def9c2be98689c8df13f6cf9452912
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