Model reference · open weights

wav2vec2-large-xlsr-53-arabic-quran-v_final

Available as managed deployment Audio rabah2026 · community Speech→text 1 variants 2k dl/mo

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 byrabah2026
TypeAudio & music
TaskSpeech→text
Parameters (lead)315M
Released2025-12-15
Popularity2k downloads / month
LicenceOpen weights

About

What wav2vec2-large-xlsr-53-arabic-quran-v_final is

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 ٰ).

Read the full model card

Utilisation

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)

Performance

  • WER (Word Error Rate) : ~4% sur 10000 echantillons des réciteurs connus et ~6% sur les reciteurs non connus.
  • Segmentation : Précision alignée pour le découpage verset par verset peut depasser 99%, tous depands de votre script de segmentation

From the published model card. Full card on the HuggingFace links in the sidebar.

Using it via the API

Call it like any OpenAI endpoint

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

Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.

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