Automatic Speech Recognition
NeMo
Arabic
speech-recognition
ASR
Arabic
Conformer
Transducer
CTC
NeMo
hf-asr-leaderboard
speech
audio
FastConformer
Hybrid
Sabeq
Eval Results (legacy)
Instructions to use MostafaAhmed98/Sabeq-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use MostafaAhmed98/Sabeq-ASR with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("MostafaAhmed98/Sabeq-ASR") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Download model.nemo from MostafaAhmed98/Sabeq-ASR: direct link, hf CLI and curl.
- Browser
- Download file 459 MB
-
https://huggingface.co/MostafaAhmed98/Sabeq-ASR/resolve/main/model.nemo
- Command line
-
hf download hf://MostafaAhmed98/Sabeq-ASR/model.nemo
-
curl -L -o model.nemo https://huggingface.co/MostafaAhmed98/Sabeq-ASR/resolve/main/model.nemo
459 MB
- Xet hash:
- 85ae9dd701b2c2a34969c518138cb0546ccc57d9ab8e747eed1524126a0f9e23
- Size of remote file:
- 459 MB
- SHA256:
- 46fb21f37a38f511d56ecfd2a7a8da7bd169e9dcbb7ee589bffa8bd9775a71f3
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