whisper-ctranslate2 0.1.2

Whisper command line client that uses CTranslate2

Introduction

Whisper command line client compatible with original OpenAI client based on CTranslate2.

It uses CTranslate2 and Faster-whisper Whisper implementation that is up to 4 times faster than openai/whisper for the same accuracy while using less memory.

Goals of the project:

• Provide an easy way to use the CTranslate2 Whisper implementation
• Easy the migration for people using OpenAI Whisper CLI

Installation

Just type:

pip install -U whisper-ctranslate2

Alternatively, the following command will pull and install the latest commit from this repository, along with its Python dependencies:

pip install git+https://github.com/jordimas/whisper-ctranslate2.git

Usage

Same command line that OpenAI whisper.

To transcribe:

whisper-ctranslate2 inaguracio2011.mp3 --model medium

To translate:

whisper-ctranslate2 inaguracio2011.mp3 --model medium --task translate

Additionally using:

whisper-ctranslate2 --help

All the supported options with their help are shown.

Whisper-ctranslate2 specific options

On top of the OpenAI Whisper command line options, there are some specific CTranslate2 options.

--compute_type {default,auto,int8,int8_float16,int16,float16,float32}

Type of quantization to use. On CPU int8 will give the best performance.

--model_directory MODEL_DIRECTORY

Directory where to find a CTranslate Whisper model, for example a fine-tunned Whisper model. The model should be in CTranslate2 format.

--device_index

Device IDs where to place this model on

--print-colors

Adding the --print_colors True argument will print the transcribed text using an experimental color coding strategy based on whisper.cpp to highlight words with high or low confidence:

Contact

Jordi Mas [e-mail]