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  1. README.md +143 -0
  2. config.json +240 -0
  3. model.bin +3 -0
  4. preprocessor_config.json +14 -0
  5. tokenizer.json +0 -0
  6. vocabulary.json +0 -0
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ - zh
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+ - de
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+ - es
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+ - ru
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+ - ko
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+ - fr
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+ - ja
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+ - pt
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+ - tr
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+ - pl
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+ - ca
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+ - nl
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+ - ar
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+ - sv
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+ - it
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+ - id
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+ - hi
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+ - fi
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+ - vi
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+ - he
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+ - uk
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+ - el
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+ - ms
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+ - cs
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+ - ro
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+ - da
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+ - hu
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+ - ta
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+ - 'no'
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+ - th
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+ - ur
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+ - hr
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+ - bg
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+ - lt
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+ - la
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+ - mi
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+ - ml
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+ - cy
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+ - sk
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+ - te
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+ - fa
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+ - lv
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+ - bn
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+ - sr
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+ - az
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+ - sl
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+ - kn
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+ - et
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+ - mk
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+ - br
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+ - eu
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+ - is
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+ - hy
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+ - ne
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+ - bs
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+ - gl
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+ - pa
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+ - si
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+ - km
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+ - yo
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+ - so
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+ - af
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+ - oc
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+ - ka
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+ - be
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+ - tg
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+ - sd
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+ - gu
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+ - am
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+ - yi
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+ - lo
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+ - uz
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+ - fo
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+ - ht
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+ - ps
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+ - tk
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+ - nn
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+ - mt
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+ - sa
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+ - lb
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+ - my
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+ - tl
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+ - mg
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+ - as
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+ - tt
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+ - haw
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+ - ln
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+ - ha
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+ - ba
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+ - jw
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+ - su
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+ - yue
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+ tags:
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+ - audio
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+ - automatic-speech-recognition
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+ license: mit
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+ library_name: ctranslate2
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+ ---
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+ # Whisper large-v3 model for CTranslate2
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+
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+ This repository contains the conversion of Whisper `large-v3` to the [CTranslate2](https://github.com/OpenNMT/CTranslate2) model format.
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+
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+ This model can be used in CTranslate2 or projects based on CTranslate2 such as [faster-whisper](https://github.com/guillaumekln/faster-whisper).
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+
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+ ## Example
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+
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+ ```python
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+ from faster_whisper import WhisperModel
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+
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+ model = WhisperModel("flyingleafe/faster-whisper-large-v3")
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+
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+ segments, info = model.transcribe("audio.mp3")
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+ for segment in segments:
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+ print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))
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+ ```
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+
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+ ## Conversion details
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+
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+ The original model was converted the following way:
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+
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+ ```
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+ # use Transformers convertation to HF format
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+ python transformers/src/transformers/models/whisper/convert_openai_to_hf.py \
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+ --checkpoint_path large-v3 --pytorch_dump_folder_path ./whisper-large-v3 --convert_tokenizer True
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+
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+ # ... some manual convertation to get `tokenizer.json` via `WhisperTokenizerFast` class ...
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+
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+ ct2-transformers-converter --model ./whisper-large-v3 --output_dir faster-whisper-large-v2 \
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+ --copy_files tokenizer.json preprocessor_config.json --quantization float16
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+ ```
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+
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+
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+ 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).
config.json ADDED
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preprocessor_config.json ADDED
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+ {
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+ "feature_extractor_type": "WhisperFeatureExtractor",
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+ "padding_value": 0.0,
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+ "processor_class": "WhisperProcessor",
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+ "return_attention_mask": false,
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+ "sampling_rate": 16000
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+ }
tokenizer.json ADDED
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vocabulary.json ADDED
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