ctranslate2-4you/whisper-base-ct2-bfloat16

🗣️ Whisper Base — CTranslate2 (bfloat16)

This is OpenAI's whisper-base converted to CTranslate2 format with bfloat16 precision.

[!TIP] Also available in other precisions: `float32` · `float16`

📋 Details

⚡ 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="base",
    compute_type="bfloat16",
    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"])

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

See the [whisper-s2t-reborn](https://github.com/BBC-Esq/WhisperS2T-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)

🇺🇸 Whisper English-Only

⚡ Distilled Whisper

🚀 Whisper Large-v3 Turbo

🔗 Links

• —📦 Inference library — whisper-s2t-reborn
• —🏗️ CTranslate2 — github.com/OpenNMT/CTranslate2
• —🧠 Original model — openai/whisper-base