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d6db305829
* added new language pairs to marian-mt * lint * seperated python code for converting tokenizers into its own file and and added a reqirements.txt for dependencies, updated instructions in readme and included python version * Cleanup. --------- Co-authored-by: Laurent <laurent.mazare@gmail.com>
37 lines
1.4 KiB
Markdown
37 lines
1.4 KiB
Markdown
# candle-marian-mt
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`marian-mt` is a neural machine translation model. In this example it is used to
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translate text from French to English. See the associated [model
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card](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-fr-en) for details on
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the model itself.
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## Running an example
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```bash
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cargo run --example marian-mt --release -- \
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--text "Demain, dès l'aube, à l'heure où blanchit la campagne, Je partirai. Vois-tu, je sais que tu m'attends. J'irai par la forêt, j'irai par la montagne. Je ne puis demeurer loin de toi plus longtemps."
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```
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```
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<NIL> Tomorrow, at dawn, at the time when the country is whitening, I will go. See,
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I know you are waiting for me. I will go through the forest, I will go through the
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mountain. I cannot stay far from you any longer.</s>
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```
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### Changing model and language pairs
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```bash
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$ cargo run --example marian-mt --release -- --text "hello, how are you." --which base --language-pair en-zh
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你好,你好吗?
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```
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## Generating the tokenizer.json files
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The tokenizer for each `marian-mt` model was trained independently,
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meaning each new model needs unique tokenizer encoders and decoders.
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You can use the `./python/convert_slow_tokenizer.py` script in this directory to generate
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the `tokenizer.json` config files from the hf-hub repos.
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The script requires all the packages in `./python/requirements.txt` or `./python/uv.lock`
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to be installed, and has only been tested for `python 3.12.7`.
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