DL Translate
dl-translate is a library for translating text between languages using transformer models.
About DL Translate
DL Translate is a Python library for translating text between languages using transformer models. It installs with pip and provides a TranslationModel class that translates text using source and target languages given as constants, names, or codes.
Users can choose mBART-50, m2m100, or NLLB-200 models with different language coverage, select the compute device, and adjust batch size. Models download from Hugging Face and are cached. The first load is slow, long texts take more time to process, and GPU use is recommended for reasonable processing time.
Key features
- Translate text using language names, codes, or constants
- Check supported languages, codes, and language-to-code mapping
- Choose between mBART-50, m2m100, and NLLB-200 models
- Select CPU, GPU, or automatic device for model loading
- Load models from Hugging Face cache or local directory
- Translate lists with adjustable batch size and progress display
Best for: Python developers who need to add text translation between languages to a script or project.
Good for
- Installs with pip and builds on Hugging Face transformer models
- Supports up to 200 languages when using NLLB-200
- Provides language constants with autocomplete and methods to list languages and codes
Watch out for
- First model load is slow
- Extremely long texts take more time to process
- Reasonable processing time generally requires a GPU
DL Translate at a glance
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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DL Translate FAQ
How do I install DL Translate?
Run pip install dl-translate.
How do I specify source and target languages?
Use dlt.lang constants, a language name such as "Arabic", or a code such as "fr" for French.
How do I select CPU or GPU?
Pass device="auto", "cpu", "gpu", or another torch.device string to TranslationModel; auto uses a GPU if possible.
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