Instructions to use Byne/whisper-large-v3-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Byne/whisper-large-v3-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Byne/whisper-large-v3-arabic")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Byne/whisper-large-v3-arabic") model = AutoModelForSpeechSeq2Seq.from_pretrained("Byne/whisper-large-v3-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train/state.json from Byne/whisper-large-v3-arabic: direct link, hf CLI and curl.
- Browser
- Download file 807 Bytes
-
https://huggingface.co/Byne/whisper-large-v3-arabic/resolve/a14c86fa031e1a3f4033b8c722abe9d3ee6cb937/train/state.json
- Command line
-
hf download hf://Byne/whisper-large-v3-arabic@a14c86fa031e1a3f4033b8c722abe9d3ee6cb937/train/state.json
-
curl -L -o state.json https://huggingface.co/Byne/whisper-large-v3-arabic/resolve/a14c86fa031e1a3f4033b8c722abe9d3ee6cb937/train/state.json
807 Bytes
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| "_fingerprint": "e873a504cf93d6cb", | |
| "_format_columns": [ | |
| "audio", | |
| "sentence" | |
| ], | |
| "_format_kwargs": {}, | |
| "_format_type": null, | |
| "_output_all_columns": false, | |
| "_split": null | |
| } |