🗣️ Whisper Tiny — CTranslate2 (float16)

This is OpenAI's whisper-tiny converted to CTranslate2 format with float16 precision.

Also available in other precisions: float32 · bfloat16


📋 Details

Base model openai/whisper-tiny
Format CTranslate2
Precision float16
Language Multilingual
Task Automatic Speech Recognition

⚡ Quick Start

Install the inference library:

pip install whisper-s2t-reborn

Transcribe an audio file:

import whisper_s2t

model = whisper_s2t.load_model(
    model_identifier="tiny",
    compute_type="float16",
    device="cuda",
)

result = model.transcribe_with_vad(
    ["audio.wav"],
    lang_codes=["en"],
    tasks=["transcribe"],
    initial_prompts=[None],
    batch_size=1,  # increase this to significantly improve throughput
)

for segment in result[0]:
    print(segment["text"])

Models are auto-downloaded from this repo the first time you run inference. No manual download required.

See the whisper-s2t-reborn repository for the full list of available parameters.


📦 All Available CTranslate2 Whisper Models

Every model below is hosted at huggingface.co/ctranslate2-4you and works with whisper-s2t-reborn.

🌍 Standard Whisper (Multilingual)

Model float32 float16 bfloat16
tiny Link Link Link
base Link Link Link
small Link Link Link
medium Link Link Link
large-v3 Link Link Link

🇺🇸 Whisper English-Only

Model float32 float16 bfloat16
tiny.en Link Link Link
base.en Link Link Link
small.en Link Link Link
medium.en Link Link Link

⚡ Distilled Whisper

Model float32 float16 bfloat16
distil-small.en Link Link Link
distil-medium.en Link Link Link
distil-large-v3 Link Link Link

🚀 Whisper Large-v3 Turbo

Model float32 float16 bfloat16
large-v3-turbo Link Link Link

🔗 Links

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