interpres 0.3.4b4

Translate from one language to another.

Interpres (Translator)

Latin Noun

interpres m or f (genitive interpretis); third declension

1. An agent between two parties; broker, negotiator, factor.

Synonyms: cōciō, arillātor

2. A translator, interpreter, expounder, expositor, explainer; dragoman.

Synonyms: coniector, commentātor, interpretātor, trānslātor

Translate from one language to another, any sentence you would like.

# Translate [FROM] [TO] [SENTENCES]
❯ translate fr "Traduisez quelle que soit la phrase que vous voulez."
Translate whatever sentence you want.

Uses Meta's NLLB model facebook/nllb-200-distilled-600M by default. You can change it by passing a custom flag --model_id.

Installation

Use pip to install Translator.

❯ pip install interpres

Or from source.

❯  pip install git+https://github.com/wasertech/Translator.git

You can also use a specific version.

❯  pip install interpres==0.3.1b4
❯  pip install git+https://github.com/wasertech/Translator.git@v0.3.1b4

Locate Translator.

❯ which translate

Usage

Using translate from your favorite shell.

❯ translate help
usage: translate [-h] [-v] [-d DIRECTORY] [-S SAVE] [-l MAX_LENGTH] [-m MODEL_ID] [-p PIPELINE] [-b BATCH_SIZE] [-n NPROC] [-e NEPOCH] [-L]
                 [_from] [_to] [sentences ...]

Translate [FROM one language] [TO another], [any SENTENCE you would like].

positional arguments:
  _from                 Source language to translate from.
  _to                   Target language to translate towards.
  sentences             Sentences to translate.

options:
  -h, --help            show this help message and exit
  -v, --version         shows the current version of translator
  -d DIRECTORY, --directory DIRECTORY
                        Path to directory to translate in batch instead of unique sentence.
  -S SAVE, --save SAVE  Path to text file to save translations.
  -l MAX_LENGTH, --max_length MAX_LENGTH
                        Max length of output.
  -m MODEL_ID, --model_id MODEL_ID
                        HuggingFace model ID to use.
  -p PIPELINE, --pipeline PIPELINE
                        Pipeline task to use.
  -b BATCH_SIZE, --batch_size BATCH_SIZE
                        Number of sentences to batch for translation.
  -n NPROC, --nproc NPROC
                        Number of process to spawn for filtering untraslated sentences.
  -e NEPOCH, --nepoch NEPOCH
                        Number of epoch(s) to translate batched sentences.
  -L, --language_list   Show list of languages.

You can translate from one language to another, any sentence you would like.

Greet Translator.

❯ translate
ℹ Welcome!
ℹ I am Translator version: 0.3.1b5
ℹ At your service.
? What would you like to translate? Manually typed sentences
ℹ Translating from: Manually typed sentences
? What language to translate from? en
ℹ Translating from eng_Latn.
? What language to translate to? fr
ℹ Translating to fra_Latn.
ℹ Preparing to translate...
Type [Ctrl] + [C] to exit.
          
What would you like to translate?
? Translate: This is a prompt-like translation shell!
C'est une coquille de traduction rapide !

What would you like to translate?
? Translate: You can quickly and effortlessly translate anything from here!
Vous pouvez traduire n'importe quoi rapidement et sans effort.

What would you like to translate?
? Translate: I hope you like my work and are considering becoming a sponsor...
J'espère que vous aimez mon travail et que vous envisagez devenir sponsor...

What would you like to translate?
? Translate:                                                                                                                                                                                 

Cancelled by user

Get Translator version.

❯ translate version

Translate from English in French.

❯ translate eng_Latn fra_Latn "This is French."
C'est français.

❯ LANG="fr_CH.UTF-8" translate en "This is also French."
C'est aussi français.

Translate from English in Spanish.

❯ translate eng_Latn spa_Latn "This is Spanish."
Esto es español.

❯ translate en es "This is also Spanish."
Esto también es español.

You can also easily translate files from a --directory and --save to a file.

❯ translate --directory . --save en2fr.txt eng_Latn fra_Latn -n 24 -e 1000 -b 64

Define:

• --nepoch (-e) as small as possible but as big as necessary.

  Translator uses this number e of epoch to determine the rate of time between updates by the amount of sentences given for translation at once.

  If this number is too small, you will face Out-Of-Memory (OOM) errors. If it is too big, you will get poor efficency.

  Keep it between 1 and the sum of sentences to translate.

  For maximum efficency keep it as low as you can while beeing able to fit epoch_split number of sentences into device's memory.

• --batch_size (-b) as big as possible but as small as necessary.

  Translator uses this value every time it needs to batch sentences to work on them.

  Mostly impacts the amount of sentences to batch togheter from epoch_split sentences to translate in one go.

  Keep it as high as possible (<epoch_split) but as low as your device memory allows to (<=1).

  For GPU using multiples of 2 is best for memory optimization (i.e. 2, 4, 8, 16, 32, 64, 128, 256, 512, etc.).

• --nproc (-n) to equal your amount of virtual threads on CPU for maximum performance.

  This value is used by translator everytime multiples sentences need to be processed by the CPU.

  Keeping it at its highest possible value, garanties maximum performances.

With a good processor and a single fast and large GPU, you can translate an average just shy of a 100 sentences per second.

On my Threadripper 2920X's 24 threads, using my RTX 3060's 12 Gb of space, I can peak at ~97 translations/second averaging a bit lower at 83.

I have not tested yet on my two RTX Titans but if you want to distribute the computation, you'll have to do it manually for now. It's in my todo list but I won't be offended if you send me a pull request to implement it.

Using Translator with python.

from translator import Translator

translator = Translator("eng_Latn", "fra_Latn")

english_sentence = "This is just a simple phrase." or [
    "Those are multiples sentences.",
    "If you have lots of them, load them directly from file.",
    "To efficiently batch translate them."
  ]
french_sentence = translator.translate(english_sentence)

print(f"{english_sentence=}")
print(f"{french_sentence=}")

Languages

Depending on models used, you might get fewer choices but with NLLB you get more than 200 most popular ones.

# translate -L
❯ translate --language_list
Language list:
    ...

From python:

>>> import translator
>>> len(translator.LANGS)
202
>>> translator.LANGS
['ace_Arab', '...', 'zul_Latn']
>>> from translator.language import get_nllb_lang, get_sys_lang_format
>>> nllb_lang = get_nllb_lang("en")
>>> nllb_lang
'eng_Latn'
>>> get_sys_lang_format()
'fra_Latn'

Checkout LANGS to see the full list of supported languages.

Using a custom model

Checkout HuggingFace Zoo of Translation Models.

Or train your own model for the translate or translate_xx_to_xx pipeline.

License

This project is distributed under Mozilla Public License 2.0.

Using this tool to translate a sentence, the licence of the original sentence still applies unless specified otherwise.

Meaning, if you translate a sentence under Creative Commons CC0, the translation is also under Creative Commons CC0.

Idem for any licence.

Contribution

I love stars ⭐ but also chocolate 🍫 so don't hesitate to sponsor this project!

Otherwise if you like the project and want to see it grow, get more convenience features like a dedicated service/client to speed up multiple translations, etc.

Don't hesitate to share your ideas by opening a ticket or even proposing a pull request.