| --- |
| language: |
| - en |
| - zh |
| - de |
| - es |
| - ru |
| - ko |
| - fr |
| - ja |
| - pt |
| - tr |
| - pl |
| - ca |
| - nl |
| - ar |
| - sv |
| - it |
| - id |
| - hi |
| - fi |
| - vi |
| - he |
| - uk |
| - el |
| - ms |
| - cs |
| - ro |
| - da |
| - hu |
| - ta |
| - 'no' |
| - th |
| - ur |
| - hr |
| - bg |
| - lt |
| - la |
| - mi |
| - ml |
| - cy |
| - sk |
| - te |
| - fa |
| - lv |
| - bn |
| - sr |
| - az |
| - sl |
| - kn |
| - et |
| - mk |
| - br |
| - eu |
| - is |
| - hy |
| - ne |
| - mn |
| - bs |
| - kk |
| - sq |
| - sw |
| - gl |
| - mr |
| - pa |
| - si |
| - km |
| - sn |
| - yo |
| - so |
| - af |
| - oc |
| - ka |
| - be |
| - tg |
| - sd |
| - gu |
| - am |
| - yi |
| - lo |
| - uz |
| - fo |
| - ht |
| - ps |
| - tk |
| - nn |
| - mt |
| - sa |
| - lb |
| - my |
| - bo |
| - tl |
| - mg |
| - as |
| - tt |
| - haw |
| - ln |
| - ha |
| - ba |
| - jw |
| - su |
| - yue |
| tags: |
| - audio |
| - automatic-speech-recognition |
| license: mit |
| library_name: ctranslate2 |
| --- |
| |
| faster-whisper officially supports the large-v3 model now. The link is [Systran/faster-whisper-large-v3](https://huggingface.co/Systran/faster-whisper-large-v3) |
|
|
| ___ |
| |
| **README.md file is based on "[guillaumekln/faster-whisper-large-v2](https://huggingface.co/guillaumekln/faster-whisper-large-v2)" and has been updated to version 3 content.** |
| |
| # Whisper large-v3 model for CTranslate2 |
| |
| This repository contains the conversion of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) 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("large-v3") |
| |
| 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-large-v3 --output_dir faster-whisper-large-v3 \ |
| --copy_files added_tokens.json special_tokens_map.json tokenizer_config.json vocab.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). |
| |
| Note that while "openai/whisper-large-v3" does not come with a "tokenizer.json" file, you can generate it using AutoTokenizer. |
| |
| ```python |
| from transformers import AutoTokenizer |
| self.hf_tokenizer = AutoTokenizer.from_pretrained("openai/whisper-large-v3") |
| self.hf_tokenizer.save_pretrained("whisper-large-v3-test") |
| ``` |
| |
| ## How faster-whisper working with Whisper-large-v3 |
| |
| **In faster-whisper version 0.10.0, there is no need to perform this handling.** |
| |
| ~~[Working with Whisper-large-v3 #547](https://github.com/guillaumekln/faster-whisper/issues/547) by. UmarRamzan~~ |
| |
| ```diff |
| - from faster_whisper import WhisperModel |
| |
| - model = WhisperModel(model_url) |
| |
| - if "large-v3" in model_url: |
| - model.feature_extractor.mel_filters = model.feature_extractor.get_mel_filters(model.feature_extractor.sampling_rate, model.feature_extractor.n_fft, n_mels=128) |
| ``` |
| |
| ## More information |
| |
| **For more information about the original model, see its [model card](https://huggingface.co/openai/whisper-large-v3).** |
| |
