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LocalAI-io/whisper-tiny-it-multi-ggml
whisper-tiny-it-multi-ggml 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.
whisper.cpp GGML quantizations of LocalAI-io/whisper-tiny-it-multi for fast CPU/GPU inference.
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Updated May 24, 2026
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From the Hugging Face model README
whisper.cpp GGML quantizations of LocalAI-io/whisper-tiny-it-multi for fast CPU/GPU inference.
Author: Ettore Di Giacinto
Brought to you by the LocalAI team. These models can be used directly with LocalAI and any whisper.cpp-based runtime.
| File | Quantization | Description |
|---|---|---|
ggml-model-f16.bin | float16 | Full precision (no quantization) — highest quality |
ggml-model-q8_0.bin | int8 | 8-bit quantization — minimal quality loss |
ggml-model-q5_0.bin | int5 | 5-bit quantization — good quality/size tradeoff |
ggml-model-q4_0.bin | int4 | 4-bit quantization — smallest size, fastest |
Fine-tuned openai/whisper-tiny (39M params) on Common Voice 25.0 + MLS + VoxPopuli + FLEURS Italian.
See LocalAI-io/whisper-tiny-it-multi for the full safetensors model and detailed WER results.
# Download a quant
huggingface-cli download LocalAI-io/whisper-tiny-it-multi-ggml ggml-model-q5_0.bin --local-dir .
# Run
./whisper-cli -m ggml-model-q5_0.bin -f audio.wav -l it
from pywhispercpp.model import Model
model = Model("ggml-model-q5_0.bin", language="it")
segments = model.transcribe("audio.wav")
for seg in segments:
print(seg.text)
# In your LocalAI model config
name: whisper-tiny-it-multi
backend: whisper
parameters:
model: ggml-model-q5_0.bin