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whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8
LocalAI-io/whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8
whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8 is a automatic speech recognition model from LocalAI-io. Use it when you need speech turned into text. The card lists the license as mit.
CTranslate2 INT8 quantized version of LocalAI-io/whisper-large-v3-it-multi-yodas-asronly-nocv for fast CPU inference.
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At a glance
- Task
- Automatic Speech Recognition
- License
- mit
- Access
- Public
- Created
- Apr 29, 2026
- Updated
- May 24, 2026
- SHA
- 131558ec
Base models
Model card
From the Hugging Face model README
whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8
CTranslate2 INT8 quantized version of LocalAI-io/whisper-large-v3-it-multi-yodas-asr_only-nocv for fast CPU inference.
Author: Ettore Di Giacinto
Brought to you by the LocalAI team. This model can be used directly with LocalAI.
Training
- Base model: openai/whisper-large-v3, fine-tuned on MLS + VoxPopuli + YODAS-Granary (asr_only) Italian
- Quantization: INT8 via CTranslate2
Usage
faster-whisper
from faster_whisper import WhisperModel
model = WhisperModel("LocalAI-io/whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8", device="cpu", compute_type="int8")
segments, info = model.transcribe("audio.mp3", language="it")
for segment in segments:
print(f"[{segment.start:.1f}s - {segment.end:.1f}s] {segment.text}")
WhisperX
import whisperx
model = whisperx.load_model("LocalAI-io/whisper-large-v3-it-multi-yodas-asr_only-nocv-ct2-int8", device="cpu", compute_type="int8")
result = model.transcribe("audio.mp3", language="it")
Links
- HF Safetensors: LocalAI-io/whisper-large-v3-it-multi-yodas-asr_only-nocv
- Code: github.com/mudler/italian-asr
- LocalAI: github.com/mudler/LocalAI
- Task
- Automatic Speech Recognition
- License
- mit
- Languages
- it
- Created
- Apr 29, 2026
- Updated
- May 24, 2026