Instructions to use dev-ahmedhany/stt_ar_fastconformer_hybrid_large_pcd_v1.0-mirror with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use dev-ahmedhany/stt_ar_fastconformer_hybrid_large_pcd_v1.0-mirror with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("dev-ahmedhany/stt_ar_fastconformer_hybrid_large_pcd_v1.0-mirror") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Mirror โ NVIDIA STT AR FastConformer Hybrid Large PCD v1.0
This is a byte-exact mirror of NVIDIAs Arabic FastConformer hybrid Transducer-CTC model with Punctuation, Capitalization, and Diacritics output (Tashkeel).
Why a mirror
This mirror exists for availability redundancy in case the upstream repo is renamed, gated, or removed. It is byte-identical to the upstream checkpoint and carries no modifications.
Source
- Upstream repo: nvidia/stt_ar_fastconformer_hybrid_large_pcd_v1.0
- Pinned upstream commit SHA:
7f32349d952f42a28dce979ba73270aa2bbdfa89 - Mirrored on: 2026-05-06
- Mirrored by: dev-ahmedhany
- License: CC-BY-4.0 (unchanged)
File integrity
sha256sum stt_ar_fastconformer_hybrid_large_pcd_v1.0.nemo
d29d19d7c054a5fc010ac6815e9cbb0dd1b21a30e0a7f7f2982e1fecaf0c3e31 stt_ar_fastconformer_hybrid_large_pcd_v1.0.nemo
Verify after download:
huggingface-cli download dev-ahmedhany/stt_ar_fastconformer_hybrid_large_pcd_v1.0-mirror \
stt_ar_fastconformer_hybrid_large_pcd_v1.0.nemo --local-dir .
sha256sum stt_ar_fastconformer_hybrid_large_pcd_v1.0.nemo
# expected: d29d19d7c054a5fc010ac6815e9cbb0dd1b21a30e0a7f7f2982e1fecaf0c3e31
Attribution (CC-BY-4.0 requirement)
Original model and weights by NVIDIA. All credit for the model architecture, training, and weights belongs to NVIDIA. This mirror simply preserves bit-for-bit access to the upstream artifact.
If you use this model, please cite the original NeMo / FastConformer papers as listed on the upstream model card.
Usage
Identical to upstream:
import nemo.collections.asr as nemo_asr
m = nemo_asr.models.EncDecHybridRNNTCTCBPEModel.from_pretrained(
"dev-ahmedhany/stt_ar_fastconformer_hybrid_large_pcd_v1.0-mirror"
)
print(m.transcribe(["audio.wav"])[0].text)
For complete usage details, training data, evaluation WER per dataset, and limitations, see the upstream model card linked above.
License
This mirror is distributed under CC-BY-4.0, the same license as the upstream NVIDIA repository. You may use, redistribute, and modify under the terms of CC-BY-4.0 with proper attribution to NVIDIA.
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