| language: | |
| - en | |
| tags: | |
| - audio | |
| - automatic-speech-recognition | |
| license: mit | |
| library_name: ctranslate2 | |
| # Whisper medium.en model for CTranslate2 | |
| This repository contains the conversion of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format. | |
| This model can be used in CTranslate2 or projects based on CTranslate2 such as [faster-whisper](https://github.com/guillaumekln/faster-whisper). | |
| ## Example | |
| ```python | |
| from faster_whisper import WhisperModel | |
| model = WhisperModel("medium.en") | |
| segments, info = model.transcribe("audio.mp3") | |
| for segment in segments: | |
| print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text)) | |
| ``` | |
| ## Conversion details | |
| The original model was converted with the following command: | |
| ``` | |
| ct2-transformers-converter --model openai/whisper-medium.en --output_dir faster-whisper-medium.en \ | |
| --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](https://opennmt.net/CTranslate2/quantization.html). | |
| ## More information | |
| **For more information about the original model, see its [model card](https://huggingface.co/openai/whisper-medium.en).** | |