From the source
Sarvam-Translate, an open-weights model, supports translation across 22 Indian languages with structured long-form text.
Now supporting 22 Indian languages and structured long-form text Download the model from Hugging Face , try it on our playground , and build with our APIs .
Making content available across languages has been a key consideration for digital accessibility.
While translation systems have continued to evolve, there remains work to be done in three broad directions - one, support for more languages; two, support for more natural translation of stylised (such as idiomatic) long-form text; and three, support for structured text in different formats.
These formats could be varied depending on the source such as a math textbook with equations, or a web page with HTML code around content, or an output of digitising an image with potential OCR-related errors.
Although multilingual large language models have demonstrated the ability to do long-form translation, their performance on Indian languages still trails behind.
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