facebook/multilingual_librispeech
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CTranslate2 INT8 quantized version of LocalAI-io/whisper-tiny-it-multi for fast CPU inference.
Author: Ettore Di Giacinto
Brought to you by the LocalAI team. This model can be used directly with LocalAI.
This model is ready to use with LocalAI via the whisperx backend.
Save the following as whisperx-tiny-it-multi.yaml in your LocalAI models directory:
name: whisperx-tiny-it-multi
backend: whisperx
known_usecases:
- transcript
parameters:
model: LocalAI-io/whisper-tiny-it-multi-ct2-int8
language: it
Then transcribe audio via the OpenAI-compatible endpoint:
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@audio.mp3" \
-F model="whisperx-tiny-it-multi"
from faster_whisper import WhisperModel
model = WhisperModel("LocalAI-io/whisper-tiny-it-multi-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}")
import whisperx
model = whisperx.load_model("LocalAI-io/whisper-tiny-it-multi-ct2-int8", device="cpu", compute_type="int8")
result = model.transcribe("audio.mp3", language="it")
Base model
openai/whisper-tiny