Model reference · open weights
wav2vec2-large-xlsr-53-arabic-quran-v_final is an open-weight audio or speech model from rabah2026. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | rabah2026 |
|---|---|
| Type | Audio & music |
| Task | Speech→text |
| Parameters (lead) | 315M |
| Released | 2025-12-15 |
| Popularity | 2k downloads / month |
| Licence | Open weights |
About
Ce modèle est une version fine-tunée de jonatasgrosman/wav2vec2-large-xlsr-53-arabic sur le dataset rabah2026/Quran-Ayah-Corpus,
Il est spécialisé pour la reconnaissance vocale du Coran (Tajweed & Murattal) et supporte l'écriture Uthmani (incluant les caractères spéciaux comme ٱ et ٰ).
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
import torch
import librosa
model_id = "rabah2026/wav2vec2-large-xlsr-53-arabic-quran-v_final"
processor = Wav2Vec2Processor.from_pretrained(model_id)
model = Wav2Vec2ForCTC.from_pretrained(model_id)
# Chargement audio (16kHz obligatoire)
audio, sr = librosa.load("verset.mp3", sr=16000)
inputs = processor(audio, sampling_rate=16000, return_tensors="pt", padding=True)
with torch.no_grad():
logits = model(inputs.input_values).logits
predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
print(transcription)
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys wav2vec2-large-xlsr-53-arabic-quran-v-final for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (wav2vec2-large-xlsr-53-arabic-quran-v-final below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="wav2vec2-large-xlsr-53-arabic-quran-v-final" -F file=@audio.mp3
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