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README.md

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+---
+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-tiny
+pipeline_tag: automatic-speech-recognition
+---
+
+# whisper-tiny-it-ct2-int8
+
+[CTranslate2](https://github.com/OpenNMT/CTranslate2) INT8 quantized version of [LocalAI-io/whisper-tiny-it](https://huggingface.co/LocalAI-io/whisper-tiny-it) 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).
+
+## Model Details
+
+- **Base model:** openai/whisper-tiny, fine-tuned on Common Voice 25.0 Italian
+- **Quantization:** INT8 via CTranslate2
+- **Size:** 39MB (vs 578MB for the original fp32 model)
+- **WER:** 27.1% on Common Voice 25.0 Italian test set
+
+## Usage
+
+### faster-whisper
+
+```python
+from faster_whisper import WhisperModel
+
+model = WhisperModel("LocalAI-io/whisper-tiny-it-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-tiny-it-ct2-int8", device="cpu", compute_type="int8")
+result = model.transcribe("audio.mp3", language="it")
+```
+
+### LocalAI
+
+This model is compatible with [LocalAI](https://github.com/mudler/LocalAI) for local, self-hosted AI inference.
+
+## Links
+
+- **HF Safetensors version:** [LocalAI-io/whisper-tiny-it](https://huggingface.co/LocalAI-io/whisper-tiny-it)
+- **Code:** [github.com/localai-org/whisper-it](https://github.com/localai-org/whisper-it)
+- **LocalAI:** [github.com/mudler/LocalAI](https://github.com/mudler/LocalAI)