Faster Whisper Base

🚀 Whisper base model for CTranslate2

This repository provides the conversion of the openai/whisper-base model to the CTranslate2 format, enabling its use in CTranslate2 and related projects.

🚀 Quick Start

This repository contains the conversion of openai/whisper-base to the CTranslate2 model format. This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.

✨ Features

• Multilingual Support: Supports a wide range of languages including English, Chinese, German, Spanish, Russian, and many more.
• Audio and ASR: Specifically designed for audio processing and automatic speech recognition tasks.
• CTranslate2 Compatibility: Can be used in CTranslate2 or projects based on CTranslate2.

💻 Usage Examples

Basic Usage

from faster_whisper import WhisperModel

model = WhisperModel("base")

segments, info = model.transcribe("audio.mp3")
for segment in segments:
    print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))

🔧 Technical Details

Conversion details

The original model was converted with the following command:

ct2-transformers-converter --model openai/whisper-base --output_dir faster-whisper-base \
    --copy_files tokenizer.json --quantization float16

Note that the model weights are saved in FP16. This type can be changed when the model is loaded using the compute_type option in CTranslate2.

📚 Documentation

For more information about the original model, see its model card.

📄 License

This project is licensed under the MIT license.