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caballosanexx/whisper-large-v3-ca-mlx
whisper-large-v3-ca-mlx is a automatic speech recognition model from caballosanexx. Use it when you need speech turned into text. It is set up for mlx. The card lists the license as apache-2.0.
MLX (Apple Silicon, fp16) conversion of projecte-aina/whisper-large-v3-ca-3catparla — a Whisper Large v3 fine-tuned on 710 hours of Catalan broadcast audio from the 3CatParla corpus.
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.npz3.1 GB · 100%
From the Hugging Face model README
MLX (Apple Silicon, fp16) conversion of projecte-aina/whisper-large-v3-ca-3catparla — a Whisper Large v3 fine-tuned on 710 hours of Catalan broadcast audio from the 3CatParla corpus.
Runs natively on Apple Silicon GPUs via mlx-whisper.
| Property | Value |
|---|---|
| Base model | openai/whisper-large-v3 |
| Fine-tune | projecte-aina/whisper-large-v3-ca-3catparla |
| Language | Catalan (ca) |
| Format | MLX fp16 |
| Size | ~2.9 GB |
| Architecture | Whisper Large v3 (32 layers, 1280 state, 20 heads) |
pip install mlx-whisper
import mlx_whisper
result = mlx_whisper.transcribe(
"audio.wav",
path_or_hf_repo="caballosanexx/whisper-large-v3-ca-mlx",
language="ca",
fp16=True,
)
print(result["text"])
Supported formats: .mp3 .wav .m4a .ogg .flac
mlx-whisperThis is an MLX format conversion of the original model. All credit for training goes to:
If you use this model in research, please cite the original work:
@inproceedings{hernandez20243catparla,
title={3CatParla: A New Open-Source Corpus of Broadcast TV in Catalan for Automatic Speech Recognition},
author={Hernández Mena, Carlos Daniel and Armentano Oller, Carme and Solito, Sarah and Külebi, Baybars},
booktitle={Proc. IberSPEECH 2024},
pages={176--180},
year={2024}
}
Apache 2.0 — inherited from projecte-aina/whisper-large-v3-ca-3catparla.