---
language: it
license: mit
tags:
- whisper
- automatic-speech-recognition
- italian
- ctranslate2
- faster-whisper
- whisperx
- localai
- int8
datasets:
- mozilla-foundation/common_voice_25_0
base_model: openai/whisper-base
pipeline_tag: automatic-speech-recognition
---

# whisper-base-it-multi-yodas-asr_only-nocv-ct2-int8

[CTranslate2](https://github.com/OpenNMT/CTranslate2) INT8 quantized version of [LocalAI-io/whisper-base-it-multi-yodas-asr_only-nocv](https://huggingface.co/LocalAI-io/whisper-base-it-multi-yodas-asr_only-nocv) for fast CPU inference.

**Author:** Ettore Di Giacinto

Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team. This model can be used directly with [LocalAI](https://localai.io).

## Training

- **Base model:** openai/whisper-base, fine-tuned on MLS + VoxPopuli + YODAS-Granary (asr_only) Italian
- **Quantization:** INT8 via CTranslate2

## Usage

### faster-whisper

```python
from faster_whisper import WhisperModel

model = WhisperModel("LocalAI-io/whisper-base-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

```python
import whisperx

model = whisperx.load_model("LocalAI-io/whisper-base-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-base-it-multi-yodas-asr_only-nocv](https://huggingface.co/LocalAI-io/whisper-base-it-multi-yodas-asr_only-nocv)
- **Code:** [github.com/mudler/italian-asr](https://github.com/mudler/italian-asr)
- **LocalAI:** [github.com/mudler/LocalAI](https://github.com/mudler/LocalAI)