This model can be used in CTranslate2 or projects based on CTranslate2 such as faster-whisper.
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))
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.
For more information about the original model, see its model card.
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Inference API does not yet support ctranslate2 models for this pipeline type.