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README.md

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+---
+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
+---
+# Whisper large-v3 model for CTranslate2
+
+This repository contains the conversion of 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("flyingleafe/faster-whisper-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 the following way:
+
+```
+# use Transformers convertation to HF format
+python transformers/src/transformers/models/whisper/convert_openai_to_hf.py \
+    --checkpoint_path large-v3 --pytorch_dump_folder_path ./whisper-large-v3 --convert_tokenizer True
+
+# ... some manual convertation to get `tokenizer.json` via `WhisperTokenizerFast` class ...
+
+ct2-transformers-converter --model ./whisper-large-v3 --output_dir faster-whisper-large-v2 \
+    --copy_files tokenizer.json preprocessor_config.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).

config.json

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+}

model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:69f74147e3334731bc3a76048724833325d2ec74642fb52620eda87352e3d4f1
+size 3087284237

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 128,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}