[Whisper] Add conversion script for the tokenizer (#27338)
* draft * updates * full conversion taken from `https://gist.github.com/xenova/a452a6474428de0182b17605a98631ee` * psuh * nits * updates * more nits * Add co author Co-authored-by: Joshua Lochner <admin@xenova.com> * fixup * cleanup * styling * add proper path * update * nits * don't push the exit * clean * update whisper doc * don't error out if tiktoken is not here * make sure we are BC with conversion * nit * Update docs/source/en/model_doc/whisper.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * merge and update * update markdwon * Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> --------- Co-authored-by: Joshua Lochner <admin@xenova.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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@@ -34,8 +34,13 @@ The original code can be found [here](https://github.com/openai/whisper).
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- Inference is currently only implemented for short-form i.e. audio is pre-segmented into <=30s segments. Long-form (including timestamps) will be implemented in a future release.
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- One can use [`WhisperProcessor`] to prepare audio for the model, and decode the predicted ID's back into text.
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This model was contributed by [Arthur Zucker](https://huggingface.co/ArthurZ). The Tensorflow version of this model was contributed by [amyeroberts](https://huggingface.co/amyeroberts).
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The original code can be found [here](https://github.com/openai/whisper).
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- To convert the tokenizer, we recommend using the following:
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```bash
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python src/transformers/models/whisper/convert_openai_to_hf.py --checkpoint_path "" --pytorch_dump_folder_path "Arthur/whisper-3" --convert_tokenizer True --whisper_version 3 --multilingual True
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```
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Here the `whisper_version` will set the number of languages to `100` to account for `cantonese` which was added in `whisper-large-v3`.
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## Inference
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